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ANALYSIS OF LOW-COST TESTING METHODS FOR LED LUMEN
MAINTENANCE OF OFF-GRID LIGHTING PRODUCTS
HUMBOLDT STATE UNIVERSITY
By
Christopher Carlsen
A Thesis
Presented to
The Faculty of Environmental Resources Engineering
In Partial Fulfillment
Of the Requirements for the Degree
Master of Science
Environmental Resources Engineering
May, 2011
ANALYSIS OF LOW-COST TESTING METHODS FOR LED LUMEN
MAINTENANCE OF OFF-GRID LIGHTING PRODUCTS
HUMBOLDT STATE UNIVERSITY
By
Christopher Carlsen
Approved by the Master‟s Thesis Committee:
Dr. Arne Jacobson, Major Professor Date
Dr. Charles Chamberlin, Committee Member Date
Dr. Eileen Cashman, Committee Member Date
Dr. Chris Dugaw, Graduate Coordinator Date
Dr. Jená Burges, Vice Provost Date
iii
ABSTRACT
ANALYSIS OF LOW-COST TESTING METHODS FOR LED LUMEN
MAINTENANCE OF OFF-GRID LIGHTING PRODUCTS
Christopher R. Carlsen
Two low-cost test methods for measuring the lumen maintenance of off-grid
lighting products, a box-photometer and a tube-photometer, were compared to a high-
accuracy integrating sphere system in order to evaluate the measurement error of the low-
cost testing devices. Results from this study indicate that the box- and tube-photometers
can be used to accurately measure the relative change in light output of typical off-grid
lighting products. The tube and box are simple and inexpensive to construct, and they are
quicker and easier to use than an integrating sphere system. The box-photometer and
tube-photometer are recommended for use in testing off-grid lighting products according
to the Long-Term Lumen Degradation Test specified in Lighting Africa‟s Quality Test
Method and Initial Screening Method.
The box‟s strengths lie in its versatility and ease-of-use. The box-photometer can
be used for testing product run-time and lumen maintenance, and a single measurement
can be conducted in a matter of seconds by a minimally trained technician. The tube-
iv
photometer, while nearly as easy to use as the box, excels in terms of constructability,
cost, and physical size. A tube-photometer can be built of basic materials that are widely
available at very low cost. No specialized tools or skills are necessary to build the
device. The tube-photometer is small, light and portable, allowing for easy storage and
minimal space for operation.
Results from this study indicate that a small degree of measurement error can
result from improper use of the low-cost devices. Box-photometer measurements are
susceptible to error caused by changes in the light source location and orientation,
especially for highly directional and adjustable products. The tube-photometer is prone
to small errors due to false identification of the maximum illuminance measurement.
These errors, however, can be easily minimized by repetition of measurements and
training test operators to use the equipment properly.
v
ACKNOWLEDGEMENTS
This research would not have been possible without the support of several
individuals and organizations over the past year. I would like to thank Dr. Arne Jacobson
for his guidance and for the opportunity to become involved in the lighting lab at Schatz
Energy Research Center (SERC). Peter Alstone at SERC was also a valuable resource, as
well as the creator of the first tube-photometer design.
A bulk of this study was conducted at the National Lighting Test Center (NLTC)
in Beijing, China, who so graciously allowed me to take over their Testing Method
Research Lab for a couple months. Thanks to Dr. Klaus Mehl at NLTC for arranging my
cooperation with NLTC. Mr. Xin Hong Zheng at NLTC was a critical player in this
research, as he took me under his wing and patiently walked me through the applicable
photometric principles and measurement methods. My work at NLTC was funded by the
National Science Foundation‟s (NSF) International Research Experience for Engineers
(IREE) program.
I would like to thank James Wafula at the University of Nairobi (UoN) in Kenya
for his participation in qualitative analysis of the test methods. Leo Blyth at Lighting
Africa was also of assistance in Nairobi, as we worked together to fabricate the box-
photometer for UoN and improve the device construction plans. Our cooperation in
Kenya and the U.S. was funded by the International Finance Corporation‟s Lighting
Africa Program.
vi
Thanks to Kevin Gauna for his steady stream of photometric testing advice and
his practical perspective on evaluating off-grid lighting products. I‟d like to acknowledge
Dr. Robert Van Kirk and Dr. Charles Chamberlin at Humboldt State University for their
assistance in the statistical analysis of the test results. My master‟s degree studies at HSU
for the 2010-2011 term were funded by the NSF through the Professional Environmental
Resources Engineering Science Master‟s Program.
vii
TABLE OF CONTENTS
ABSTRACT ....................................................................................................................... iii
ACKNOWLEDGEMENTS .................................................................................................v
TABLE OF CONTENTS .................................................................................................. vii
LIST OF TABLES ............................................................................................................. xi
LIST OF FIGURES ......................................................................................................... xiii
LIST OF APPENDICIES ............................................................................................... xvii
INTRODUCTION ...............................................................................................................1
Objectives .................................................................................................................... 3
Structure of Thesis ....................................................................................................... 4
1 BACKGROUND .............................................................................................................6
1.1 Off-grid Lighting in Sub-Saharan Africa ......................................................... 7
1.2 Fuel-based Lighting .......................................................................................... 8
1.3 Off-Grid Lighting Products (OLPs) ............................................................... 10
1.3.1 Currently Available OLPs ................................................................... 12
1.3.2 Market Spoilage ................................................................................... 14
1.3.3 OLP Market ......................................................................................... 16
1.4 Lighting Africa – Catalyzing Markets for Modern Lighting .......................... 20
1.5 OLP Quality Assurance .................................................................................. 21
1.5.1 Lighting Africa Quality Test Method (QTM) ..................................... 22
1.5.2 Lighting Africa Initial Screening Method (ISM) ................................ 25
1.6 OLP Systems .................................................................................................. 26
viii
1.6.1 Energy Conversion: Photovoltaic Modules ......................................... 28
1.6.2 Batteries ............................................................................................... 29
1.6.3 Control Circuitry.................................................................................. 30
1.6.4 Light Emitting Diodes (LEDs) ............................................................ 31
1.6.5 Lumen Maintenance of LEDs .............................................................. 35
1.6.6 Lumen Maintenance Testing ............................................................... 37
1.7 Photometry...................................................................................................... 41
1.7.1 Luminous Flux ..................................................................................... 43
1.7.2 Luminous Intensity .............................................................................. 44
1.7.3 Illuminance .......................................................................................... 44
1.7.4 Determining Luminous Flux of a Light Source................................... 45
1.8 Light Measuring Devices ................................................................................ 46
1.8.1 Spectroradiometer ................................................................................ 46
1.8.2 Illuminance meter ................................................................................ 47
1.8.3 Goniophotometer ................................................................................. 47
1.8.4 Integrating Sphere ................................................................................ 48
1.8.5 Box-Photometer ................................................................................... 54
1.8.6 Tube-Photometer ................................................................................. 58
2 MATERIALS AND METHODS ..................................................................................60
2.1 Materials ......................................................................................................... 60
2.1.1 Devices under Test (DuTs) .................................................................. 60
2.1.2 LED Driver .......................................................................................... 62
2.1.3 Box-Photometer ................................................................................... 63
ix
2.1.4 Tube-Photometer ................................................................................. 65
2.1.5 Integrating Sphere – Spectroradiometer System ................................. 66
2.2 Integrating Sphere Calibration ........................................................................ 68
2.2.1 Measuring non-uniform reflectance of interior sphere surface ........... 69
2.2.2 Correcting for Light Distribution Mismatch ....................................... 70
2.2.3 Correcting for Self Absorption ............................................................ 73
2.2.4 Color Mismatch ................................................................................... 74
2.3 Simulated Lumen Maintenance Test .............................................................. 76
2.3.1 Experimental Design ........................................................................... 78
2.3.2 Driving the DuT................................................................................... 80
2.3.3 Determining the LED Nominal Drive Current .................................... 80
2.3.4 Adjusting the LED Drive Current ....................................................... 81
2.3.5 DuT Orientation ................................................................................... 82
2.3.6 DuT Testing Order............................................................................... 82
2.3.7 Ambient Temperature Regulation ....................................................... 83
2.3.8 Integrating Sphere Procedure .............................................................. 83
2.3.9 Box-Photometer Procedure.................................................................. 84
2.3.10 Tube-Photometer Procedure ................................................................ 85
3 RESULTS ......................................................................................................................87
3.1 Calibration Plots ............................................................................................. 87
3.2 Relative Change in Initial Light Output ......................................................... 90
3.3 Box-Photometer Calibration Plots .................................................................. 92
3.4 Tube-Photometer Calibration Plots ................................................................ 96
x
3.5 Relative Change in Initial Light Output ......................................................... 99
3.6 Statistical Analysis of Test Data ................................................................... 101
3.6.1 Standard Error of Regression for Calibration Plots ........................... 101
3.6.2 95% Confidence Intervals of the Calibration Plot ............................. 103
3.6.3 Error in Relative Light Output Calculations...................................... 107
3.6.4 Analysis of Variance (ANOVA) for R2 of Calibration Plots ............ 109
4 DISCUSSION OF RESULTS .....................................................................................120
4.1 Worst Case: Error Analysis of Firefly in the Box-Photometer ................... 121
4.2 Sources of Error ............................................................................................ 123
5 CONCLUSIONS AND RECOMMENDATIONS ......................................................125
5.1 Impact of Error on Lumen Maintenance Test Results .................................. 125
5.2 Benefits and Disadvantages of the Box-Photometer .................................... 126
5.3 Benefits and Disadvantages of the Tube-Photometer ................................... 128
5.4 Multiple Test Operators ................................................................................ 129
5.5 Potential Improvements to Lumen Maintenance Testing Devices ............... 130
REFERENCES ................................................................................................................133
xi
LIST OF TABLES
Table 1: Specifications of Devices under Test (DuTs) used in the Simulated Lumen
Maintenance Test. .............................................................................................62
Table 2: Summary of the light distribution mismatch correction for the DuTs. ...............73
Table 3: Auxiliary lamp luminous flux measurements for all of the light sources
according to body color. ....................................................................................76
Table 4: Structure of the Simulated Lumen Maintenance Test. .......................................79
Table 5: Calibration plots whose linear models do not pass through the origin within the
95% confidence interval.. ................................................................................107
Table 6: Summary of null hypotheses tested in ANOVA and interpretation of the
statistical test results. .......................................................................................109
Table 7: Hierarchy of experimental design for ANOVA................................................113
Table 8: Summary of the categorical predictor variables used in the Simulated Lumen
Maintenance test statistical analysis. ...............................................................113
Table 9: Statistical results from the general linear model for the transformed R2 values of
the calibration plots. ........................................................................................117
Table 10: Illuminance map describing irregularity in the interior integrating sphere
surface used in testing. ....................................................................................140
Table 11: Raw data from comparison testing of the Firefly product in the integrating
sphere, box-photometer and tube-photometer. ................................................149
Table 12: Raw data from comparison testing of the Kiran product in the integrating
sphere, box-photometer and tube-photometer. ................................................150
Table 13: Raw data from comparison testing of the Solux product in the integrating
sphere, box-photometer and tube-photometer. ................................................151
Table 14: Raw data from comparison testing of the Aishwarya product in the integrating
sphere, box-photometer and tube-photometer. ................................................152
xii
Table 15: Maximum error in the calculation of relative decrease in the initial light output
according to light source, round of testing, testing apparatus, and orientation
within the box-photometer. .............................................................................159
Table 16: R-squared values, standard error of the linear regression, and the standard error
as a percentage of the average luminous flux estimated by the linear regression
model for each round of Simulated Lumen Maintenance testing ...................166
xiii
LIST OF FIGURES
Figure 1: Total cost of illumination services for select off-grid lighting products. ..........12
Figure 2: Solar Portable Light (SPL) Quality Matrix that describes the range of solar
charged portable lighting products according to the autonomous run time .....14
Figure 3: Solar Portable Light (SPL) market growth scenarios ........................................19
Figure 4: Conceptual system description of a typical off-grid lighting product. ..............27
Figure 5: Off-grid lighting product solar panel prices are expected to continue rapid cost
decline ..............................................................................................................29
Figure 6: Electrical model of a light emitting diode (LED). .............................................32
Figure 7: Components of a typical through-hole type LED package.. .............................32
Figure 8: Trends and projections for luminous efficacy of commercially available cool
and warm white LEDs .....................................................................................34
Figure 9: Electromagnetic spectrum, including the range of visible light wavelengths
detectable by the human eye. ...........................................................................41
Figure 10: V-lambda curve describing the sensitivity of the „standard observer‟ (i.e.
typical human vision) to different wavelengths in the visible spectrum. ........43
Figure 11: Lamp measurement sphere using a detector mounted directly at the view port
..........................................................................................................................50
Figure 12: Box-photometer. ..............................................................................................55
Figure 13: Optimal measuring configuration for a box-photometer. ................................57
Figure 14: Line drawing of a tube-photometer, indicating the basic device components.
..........................................................................................................................58
Figure 15: Current shunt circuit used to measure current through the LEDs. ..................63
Figure 16: Tube-photometer similar to that used in the study. .........................................65
Figure 17: Example of the software output for a measurement of the Firefly luminous
flux.. .................................................................................................................67
xiv
Figure 18: Device for measuring the reflectance characteristics of the integrating
sphere‟s interior surface. ..................................................................................70
Figure 19: Computer rendering of the simplified three dimensional light distribution
shapes for the standard lamp, Solux, Firefly, Kiran, and Aishwarya ..............72
Figure 20: Photos of self absorption color dependency measurements using the
integrating sphere .............................................................................................76
Figure 21: Tube calibration plot for one round of measurements with the Firefly...........88
Figure 22: Relative change in initial light output for the Firefly, as measured by the
integrating sphere and the tube-photometer. ....................................................91
Figure 23: Box-photometer calibration plot for the Firefly ..............................................94
Figure 24: Box-photometer calibration plot for the Kiran ................................................94
Figure 25: Box-photometer calibration plot for the Solux................................................95
Figure 26: Box-photometer calibration for the Aishwarya ...............................................95
Figure 27: Tube-photometer calibration plot for the Firefly ............................................97
Figure 28: Tube-photometer calibration plot for the Kiran ..............................................97
Figure 29: Tube-photometer calibration plot for the Solux ..............................................98
Figure 30: Tube-photometer calibration plot for the Aishwarya ......................................98
Figure 31: Plots of measured relative luminous flux decrease as a percentage of the
original light output for Firefly over three rounds of testing. ........................100
Figure 32: Tube calibration plot for the second round of testing with the Firefly,
including the best fit line and 95% confidence interval bounds ....................104
Figure 33: Enlarged section of the tube calibration plot for the Firefly. ........................105
Figure 34: Box calibration plot for round 3 of testing the Firefly with the light directed at
the lid of the box, including the linear model and the 95% confidence interval
bounds ............................................................................................................105
Figure 35: Lumen depreciation plot for the third round of testing with the Aishwarya..
........................................................................................................................108
Figure 36: Histogram of R-squared values for the experimental calibration plots .........112
xv
Figure 37: Residual plots of the R-squared values for the experimental calibration plots.
........................................................................................................................115
Figure 38: Histogram of R2 data after applying the transformation shows normal
distribution. ....................................................................................................116
Figure 39: Interaction plot showing how the mean R2 value varies across the box- and
tube-photometer testing methods and four light sources. ..............................119
Figure 40: Light measurement apparatus used at the Lighting Research Center for lumen
maintenance and run time testing of off-grid lighting products ....................131
Figure 41: Off-grid lighting products used in this study.................................................138
Figure 42: Radial light distribution of the Firefly product .............................................142
Figure 43: Radial light distribution of the Aishwarya product .......................................142
Figure 44: Radial light distribution of the Solux product ...............................................143
Figure 45: Radial light distribution of the Kiran product ...............................................143
Figure 46: Radial light distribution of the standard lamp ...............................................144
Figure 47: Plots of measured relative luminous flux decrease for Firefly for three rounds
of testing.........................................................................................................154
Figure 48: Plots of measured relative luminous flux decrease for Kiran for three rounds
of testing.........................................................................................................155
Figure 49: Plots of measured relative luminous flux decrease for Solux for three rounds
of testing.........................................................................................................156
Figure 50: Plots of measured relative luminous flux decrease for Aishwarya for three
rounds of testing. ............................................................................................157
Figure 51: Comparison of integrating sphere lumen measurement to tube- and box-
photometer lux measurements for each round of Firefly Simulated Lumen
Maintenance testing. ......................................................................................161
Figure 52: Comparison of integrating sphere lumen measurement to tube- and box-
photometer lux measurements for each round of Kiran Simulated Lumen
Maintenance testing. ......................................................................................162
xvi
Figure 53: Comparison of integrating sphere lumen measurement to tube- and box-
photometer lux measurements for each round of Solux Simulated Lumen
Maintenance testing. ......................................................................................163
Figure 54: Comparison of integrating sphere lumen measurement to tube- and box-
photometer lux measurements for each round of Aishwarya Simulated Lumen
Maintenance testing. ......................................................................................164
xvii
LIST OF APPENDICIES
APPENDIX A: LIGHT SOURCES USED IN TESTING .............................................137
APPENDIX B: INTEGRATING SPHERE INTERNAL REFLECTANCE MAP ........139
APPENDIX C: DUT LIGHT DISTRIBUTION .............................................................141
APPENDIX D: INTEGRATING SPHERE PROCEDURE ...........................................145
APPENDIX E: RAW TEST DATA ...............................................................................148
APPENDIX F: RELATIVE LUMEN DECREASE PLOTS ..........................................153
APPENDIX G: MAXIMUM ERROR IN RELATIVE LUMEN DECREASE .............158
APPENDIX H: CALIBRATION PLOTS ......................................................................160
APPENDIX I: STANDARD ERROR OF TEST RESULTS .........................................165
APPENDIX J: BOX-PHOTOMETER CONSTRUCTION PLANS AND
INSTRUCTIONS ..................................................................................168
APPENDIX K: TUBE-PHOTOMETER CONSTRUCTION PLANS ..........................176
APPENDIX L: LIST OF EQUIPMENT USED IN THE STUDY .................................178
1
INTRODUCTION
Kerosene-fueled lamps and candles are the main sources of light for
approximately 600 million people (69.5% of the population) in Sub-Saharan Africa who
lack access to electricity (International Energy Agency, 2010). Every year, African
households and small businesses spend upwards of $17 billion on lighting (Lighting
Africa, 2010d). Many low-income African households spend approximately 2% of their
income on fuel for lighting (Mills, 2005; World Bank, 2009).1 Not only does this
population spend a significant portion of their household income on fuel, but they are
consequently subjected to poor light quality and health hazards due to emission of air
pollutants (Apple, 2010; Mills, 2005). A transition away from dirty, inefficient kerosene
combustion will drastically reduce the environmental, health and economic problems
resulting from current off-grid lighting practices.
Recent technological advancement and decreasing cost of Light Emitting Diodes
(LEDs), photovoltaic (PV) modules, and rechargeable batteries offer a potentially
sustainable means of addressing the multi-faceted problem of off-grid lighting in Sub-
Saharan Africa. Clean, efficient and reliable; off-grid lighting products (OLPs) are
beginning to gain a foothold in a market dominated by fuel-based lighting. New OLPs
are entering the market with affordable prices that may position them to replace fuel-
1 Percent of household income dedicated to the purchase of kerosene for fuel-based lighting calculated
based on 3.2 L/month-person kerosene consumption, $0.50/Liter of kerosene, and $1,125 gross national
income per capita.
2
based lighting in Sub-Saharan Africa and throughout the developing world.
Unfortunately, the off-grid lighting market is becoming flooded with poor quality
products. Inferior goods are contributing to “market spoilage,” whereby low-income
end-users sustain significant financial losses due to rapid failure of the lighting products.
Negative experiences undermine consumer confidence, ultimately creating a barrier to
the widespread adoption of LED products (Lighting Africa 2010c; Tracy, 2010).
In an effort to reduce market spoilage, the author has been working with the
Schatz Energy Research Center (SERC) and the National Lighting Test Center (NLTC)
to develop a standardized method for testing the performance of off-grid lighting
products. SERC is working with Lighting Africa, a project of the World Bank Group, to
establish an internationally accepted testing protocol and performance standards that will
be used for certification of off-grid lighting products. This testing method, currently
titled Lighting Africa Quality Test Method (QTM), is the culmination of contributions
made by Fraunhofer Institute for Solar Energy Systems (FISE), SERC, NLTC and
others.2
This thesis specifically addresses the QTM lumen maintenance test, referred to as
the Long-Term Lumen Degradation Test, which is conducted to evaluate the irreversible
decrease in light output from a light source over time. Tests performed by Lighting
Africa have indicated that some LED lighting products on the market will lose a large
percentage of their light output in the first few days or months of operation (Lighting
2 The most recently published version of the QTM is available for download online at
http://lightingafrica.org/resources/technical-research.html
3
Africa, 2010b). The lumen maintenance test is designed to distinguish between products
that experience rapid lumen depreciation and those that are able to provide thousands of
hours of lighting service. Verifying that an OLP can maintain appropriate levels of light
output instills confidence in the consumer that over its lifetime, the product will cost less
than fuel-based alternatives.
The photometric industry standard method for determining lumen maintenance of
a lighting product established by the Illuminating Engineering Society (IES) requires
expensive, specialized equipment and training that is generally not accessible to Lighting
Africa‟s affiliates in developing countries (IES, 2008). The Long-Term Lumen
Degradation Test that is being developed by Lighting Africa utilizes relatively simple
and inexpensive devices that are more appropriate for testing centers and manufacturers
with small budgets.
Objectives
This research compares the measurement accuracy of two low-cost light
measuring devices to a spectroradiometer-integrating sphere system, which is the
photometric industry standard testing apparatus. One low-cost apparatus, a box-
photometer, was custom built according to specifications described in the QTM (Lighting
Africa, 2010c). The other low-cost device, a tube-photometer, was custom made
according to a prototype developed at SERC. The three testing devices were used to
conduct parallel measurements of the light output from four different OLPs. Illuminance
4
measurements made with the box- and tube-photometers are compared to the luminous
flux determined with the integrating sphere over a range of light output levels.
„Calibration plots‟ were generated for each round of testing in order to evaluate how
closely the low-cost devices replicate the integrating sphere measurements. Statistical
analysis of the test results is used to describe the behavior of the systems under different
conditions, including varying light levels, spatial light distributions, and physical size.
The box- and tube-photometers are also evaluated qualitatively in terms of ease of use,
repeatability and general appropriateness for use in the QTM. The ultimate objective of
this research is to provide Lighting Africa and the off-grid lighting industry with well-
supported recommendations for improving the Long-Term Lumen Degradation Test.
Structure of Thesis
To put this research in context, Sections 1.1 and 1.2 begin with a general
overview of off-grid lighting in Sub-Saharan Africa. Section 1.3 I addresses the typical
forms of fuel-based lighting as well as OLPs that have been recently entering the market.
A broad overview of the current OLP market and forecasts for market development over
the coming decade are presented. Lighting Africa and the quality assurance strategy to
which this research directly applies is then introduced in Sections 1.4 and 1.5. Beginning
in Section 1.6, the thesis delves into a technical, component-level evaluation of OLP
systems, with an emphasis on LEDs and the phenomenon of lumen depreciation. Next,
Sections 1.7 and 1.8 describe the basic photometric concepts and devices that are used in
5
this research. After laying out the setting and general scientific principles associated with
this study, the specific materials and methods used to compare the accuracy of the lumen
maintenance testing apparatuses are outlined in Section 2. The experimental data from
this research are presented in Section 3, including statistical analysis of the results.
Finally, in Sections 4 and 5 the results are interpreted and conclusions are drawn about
the use and appropriateness of low-cost lumen maintenance test methods for OLP quality
assurance testing.
6
1 BACKGROUND
The underlying premise of this study is that lighting is a human necessity. Since
the discovery of fire, human development has been inextricably linked to artificial light.
Without light sources that range from a simple fire, to modern incandescent, fluorescent,
and LED luminaires, we would not have achieved the levels of general well-being and
productivity that most of us take for granted. In his 2005 article about off-grid lighting,
Evan Mills states that “illumination is one of the core end-use services sought by society”
(Mills, 2005).
The narrow focus of this research, low-cost testing of OLP lumen maintenance, is
a small but important issue in the big picture of delivering affordable, high quality
lighting service to low income people in Sub-Saharan Africa and throughout the
developing world. In fact, lumen maintenance testing of off-grid lighting products is
only one of a suite of tests included in Lighting Africa‟s Quality Test Method (Lighting
Africa, 2010c). In order to understand the importance of quality assurance testing of off-
grid lighting products, and specifically lumen maintenance testing, one must first
understand the context in which the testing occurs.
7
1.1 Off-grid Lighting in Sub-Saharan Africa
Joseph Conrad‟s 1902 novel, Heart of Darkness, alludes in part to the dark
African nights before the dawn of modern illumination. While much has changed since
the late 19th
century, much of Sub-Saharan Africa is still literally in the dark. Currently,
585.2 million people in Sub-Saharan Africa lack access to electricity (International
Energy Agency, 2010). Expansion of the electric grid to rural areas in developing
countries has proven to be very slow due to low load densities, coupled with high capital
costs and low efficiencies associated with thermal power generation (Mills, 2005). The
IEA forecasts that by 2030 Africa‟s un-electrified population will grow to 700 million
(International Energy Agency, 2010).
Some have turned to solar home systems (SHS) as a solution to the energy access
dilemma. The market for SHS has experienced growth in Sub-Saharan Africa (Lighting
Africa, 2010d). The cost of system components is dropping and quality is improving, yet
SHS still remain financially out of reach for many of Africa‟s rural poor and this is not
expected to change in the next decade (GTZ, 2010). Households that are able to afford
SHS, however, may only allocate a small proportion of the energy to lighting. A 2004
study on rural electrification in Kenya asserts “that in many households, especially those
with small systems, intra-household dynamics constrain key social uses (e.g. children‟s
studying), as the energy is allocated to other uses” (Jacobson, 2007).
8
1.2 Fuel-based Lighting
For the nearly 70% of Sub-Saharan Africans that do not have grid electricity, fuel-
based light sources like wick lamps and candles are a common means of household and
commercial illumination. Fuel-based lighting has dominated the market due to the
availability of fuels and lamps, as well as the relatively low initial and recurring costs of
operation. Even very rural villages have access to fuel-based lighting, and fuel can be
purchased in small, affordable quantities. Simple, low-cost and robust lamps are
available in rural markets. Candles are also a common commodity. Inexpensive wick
lamps can be fashioned from recycled metal cans with basic hand tools. From the
perspective of a low-income rural household living without electricity, fuel-based
lighting makes sense. The consumers may not fully consider, however, a laundry list of
negative impacts associated with burning biomass and fossil fuels for light.
From an economic standpoint, the average low-income African family spends
approximately 2% of their monthly budget on recurring fuel expenses for lighting (Mills,
2005; World Bank, 2009). With an enormous population off the grid, these fuel expenses
add up. In 2005, Evan Mills estimated that fuel-based lighting is responsible for annual
energy consumption of 77 billion liters of fuel worldwide (or 2800 petajoules, PJ), at a
cost of $38 billion/year or $77 per household (Mills, 2005). Price volatility due to
instability of subsidy regimes and ongoing increases in kerosene prices, estimated at 4%
annually over the next few years, will make fuel-based lighting less and less attractive
(Lighting Africa, 2010d).
9
When evaluated in terms of the illumination provided, fuel-based lighting proves
to be inadequate and expensive. The amount of light emitted from candles and wick
lanterns is too low for many basic tasks. A simple wick lantern provides about 1 lux
(lumens/m2) at 1 meter from the source, compared with levels on the order of 500 lux
routinely provided in industrialized countries (Mills, 2005). Mills also estimates that the
cost per unit of useful lighting energy service delivered ($/lux-hour of light, including
capital and operating costs) for fuel-based lighting is up to ~150 times that for premium
efficiency fluorescent lighting (Mills, 2005).
Fuel-based lighting also raises health concerns. Combustion of biomass and fossil
fuels emits particulate matter into the air that increases the risk of respiratory illnesses. A
recent study led by Dustin Poppendieck found that vendors who use a single simple wick
lamp in high-air-exchange market kiosks will likely be exposed to levels of PM2.5
(particulate matter with a diameter less than or equal to 2.5 m) that are an order of
magnitude greater than ambient health guidelines (Apple et al., 2010) . When placed in
homes with lower air exchange rates, fuel-based lights can lead to even higher
concentrations of respirable particulate matter in the air.
It is also well known that burning fossil fuels emits greenhouse gases into the
atmosphere. A single kerosene lamp that is used four hours per day emits over 100 kg of
CO2 into the atmosphere each year (Mills, 2005). Evan Mills found that the combustion
of fuel for lighting results in 190 million metric tonnes per year of carbon dioxide
emissions, equivalent to one-third the total emissions from the U.K. (Mills, 2005).
10
1.3 Off-Grid Lighting Products (OLPs)
Increasing fuel prices as well as health and environmental concerns are shifting
consumers‟ attention towards alternatives to fuel-based lighting. With SHS prices still
too high and grid electrification too far away, some low-income households in Sub-
Saharan Africa are purchasing off-grid lighting products (OLPs). A working definition
of OLPs for this research is based on a description of “solar portable lights” presented by
Lighting Africa in their recent publication, titled Solar Lighting for the Base of the
Pyramid. OLPs can be differentiated from SHS and other small scale lighting devices
according to function, technology, and quality.
Function - Lighting systems range from the task specific (torches/flashlights) to the
general ambient lighting functions. These products can include added functions such
as mobile phone charging, but light has to be the primary design driver. The
functionality also has to allow easy portability and therefore is distinct from the solar
home system market.
Technology - The light – typically LED-based, though many products still feature CFL
bulbs – has to be rechargeable.
Quality - Recognizing the emerging issue of market spoilage from poor quality products,
[this] analysis excludes ultra-cheap (typically battery-powered, nonsolar) LED
torches/flashlights ($1-10), which have experienced substantial sales over the past few
years in Africa (Lighting Africa, 2010d).
Although relatively new to the market, high quality OLPs have already proven to
offer substantial benefits to off-grid households in Sub-Saharan Africa. Evan Mills
succinctly touts the advantages of solar powered LED lights: “WLED [White Light
Emitting Diode] technologies provide more and better illumination (with easier optical
11
control) than do fuels, dramatically reducing operating costs and greenhouse gas
emissions, while increasing the quality and quantity of lighting services” (Mills, 2005).
The light output by LEDs in currently available OLPs ranges between about 20
and 70 lumens, compared to 12 lumens emitted from a typical candle (Lighting Africa,
2010a). Well designed OLPs also deliver higher quality light. Commonly available
LEDs and inexpensive optics are capable of providing a highly uniform light distribution
with color rendering and color temperatures that are superior to most fuel-based lights.
Over the lifetime of an OLP, the cost of lighting service ($/lux-hour) is much less
than fuel-based lights. Mills‟ research indicates that OLPs can be the most cost effective
solution for off-grid applications. Figure 1 shows that the cost of lighting service for a
typical OLP is not only drastically less than fuel-based lights, but is also slightly less than
fluorescent and incandescent lamps in grid-connected homes.
12
Figure 1: Total cost of illumination services for select off-grid lighting products. Costs include
equipment purchase price amortized over three years, fuel, electricity, wicks, mantles, replacement
lamps and batteries. Assumptions are four hours/day operation over a one year period in each case,
$0.1/kWh electricity price, $0.5/liter fuel price (reproduced from Mills, 2005).
1.3.1 Currently Available OLPs
As the OLP market matures, manufacturers have begun to sell products that cater
to the specific demands of consumers in Sub-Saharan Africa. Improvements in
technology, decreasing component costs and continued product development will surely
yield OLPs of diverse form and function. Nonetheless, familiarity with the current OLPs
is needed in order to understand the context in which this thesis research was conducted.
13
Lighting Africa‟s experience with products that are currently available in Sub-
Saharan Africa has shown that OLPs fall into the following general categories:
Flashlights/Torches - portable handheld devices offering directional lighting at low
lumen output.
Task lamps/work lights – portable or stationary handheld devices, including desk
lamps, in a range of light output levels utilized for specific tasks (i.e. reading,
weaving etc.).
Ambient lamps /“lanterns” – portable or stationary devices that resemble the kerosene
hurricane lamp form factor. They typically offer multi-directional light along with a
wide variety of size and functionality depending on technology (e.g., from heavy,
powerful CFL lanterns to smaller LED-based systems).
Multi-functional devices – portable or stationary devices that can provide directional
and multi directional light, a variety of value-added features (i.e. mobile phone
recharge), and can be utilized for either task based or ambient lighting needs.
Micro-SHS – semi-portable lighting devices associated with a small portable solar
panel that powers or charges 1-3 small lights, mobile phones, and other low-power
accessories (e.g., radio, mini-fan) (Lighting Africa, 2010d).
A quality matrix is a useful way to view the variety of OLP options on the market.
Data from the Renewable Energy and Energy Efficiency Partnership (REEEP) and
Lawrence Berkley National Laboratory has been compiled to create a quality matrix of
battery life vs. lumen output for 12 different “Solar Portable Lights” (SPLs). Shown in
Figure 2; the SPL Quality Matrix demonstrates the range of performance and
corresponding prices that have been witnessed in the market. While this thesis addresses
the broader category of off-grid lighting (both solar-powered and non-solar-powered
products), the SPL Quality Matrix is indicative of the general state of the off-grid lighting
market as a whole. The plot indicates that even in its infancy, the OLP market has begun
to develop segments according to price and performance.
14
Figure 2: Solar Portable Light (SPL) Quality Matrix that describes the range of solar charged
portable lighting products according to the autonomous run time (i.e. the amount of time that the
OLP provides useable light on a fully charged battery) and the luminous flux (i.e. the total power of
light emitted by the OLP when fully charged)(reproduced from Lighting Africa, 2010c).
1.3.2 Market Spoilage
Not shown in Figure 2 are the products in the $1-$10 range that are of extremely
poor quality. Most of these cheap products exhibit endemic failures that arise from low
quality components, poor design, and poor craftsmanship. OLPs that quickly break or fail
to function properly are causing market spoilage, wherein “consumers have increasingly
become cautious and have at times chosen to continue using kerosene lamps, the
economic, health and social disadvantages notwithstanding” (Lighting Africa, 2010d).
15
Market spoilage is a serious concern for the growth of the high quality OLP
market. Component costs are decreasing and performance is improving to the point
where high quality OLPs are becoming physically and economically accessible to low
income households in Sub-Saharan Africa. Yet, the wide availability of cheap, low
quality lights threatens to bias the consumers against OLPs, regardless of quality. When
a modern lighting product rapidly fails, the total cost of illumination service can be much
higher than fuel-based alternatives.
With large numbers of poor quality lighting products available, African
consumers have already developed some bias against OLPs. A study conducted in 2007
indicated that some degree of market spoilage was probably already occurring at that
time (Mills & Jacobson, 2008). The good news is that all sectors of the off-grid lighting
market are not completely spoiled. Many new high quality products with affordable
retail prices are entering the market. OLPs are being manufactured by a range of
companies, from small social entrepreneurs to large, multinationals. Lighting Africa
expects that some extent of consumer education will occur naturally as higher quality
OLPs gain a larger market share. Field studies offer evidence that the willingness to pay
for quality OLPs increases as much as fivefold with experience (Lighting Africa, 2010d).
16
1.3.3 OLP Market
Currently, the market penetration of OLPs in Africa is relatively low. Recent
studies by the World Bank and Dalberg Global Development Advisors estimates that
market penetration of solar lighting products is currently around 1%, with less than a
0.5% share for solar portable lights (Lighting Africa, 2010d). The OLP market, however,
is still young and rapid growth is expected over the coming years. In a recent interview
with the New York Times, Stewart Craine, co-founder of Barefoot Power, which has sold
solar desk lamps and other clean lighting products to 120,000 households in Africa and
elsewhere, likened the current OLP market to the African mobile phone market. Craine
said that the OLP industry, while worth less than $1 billion now, is about the same size of
the African mobile phone industry in the 1990s. Africa is now the fastest-growing mobile
phone market in the world. This comparison is encouraging for both the rural poor and
companies in the OLP industry. Craine quoted, "We would expect precisely the same
behavior from the microenergy market in the next five or 10 years, and that's what's
going to reach a lot of people, even if we haven't reached a whole lot just yet" (Friedman,
2010).
Recent studies by Lighting Africa and the German Company for International
Cooperation (GTZ) suggest that the OLP market will experience rapid growth over the
coming years. In their 2010 publication titled “What difference can a PicoPV system
make?” GTZ lists several reasons why PicoPV systems (small-scale, solar powered
OLPs) are expected to rapidly replace fuel-based lights in Sub-Saharan Africa:
17
Pico PV prices are coming down fast.
Pico PV systems are over-the-counter consumer products and don‟t need specific
know-how for installation or O&M. Therefore, distribution has lower transaction
costs than for all other grid or off-grid alternatives.
The welfare gain from electrification at household level is arguably largest after
stepping from flame-based lighting to efficient electric lights.
Consumers do not fear that Pico PV lamps will bar them from future grid roll-out,
as they often do in the case of SHSs (GTZ, 2010).
Lighting Africa‟s analysis in their 2010 SPL market report suggests that the
African market for off-grid renewable lighting will experience exceptional growth.
Based on current growth trends, the market will easily experience 40-50% annual sales
growth, and 5-6 million African households will own OLPs by 2015 (Lighting Africa,
2010d). Lighting Africa projects that “by 2015, SPLs that are of the same cost as
currently available products will be more robust, lighter weight, longer lasting,
environmentally cleaner, and two to three times brighter than today‟s SPLs” (Lighting
Africa, 2010d). More specifically, projections indicate that the manufactured cost of
OLPs will decrease by 40% in the next five years and the consumer payback period will
be in the range of two to eight months (Lighting Africa, 2010d). Additional growth of
the OLP market beyond the conservative projection is expected to come from
technological advancements, entrepreneurial innovation, improved distribution networks
and financing mechanisms.
The OLP market may be further supported by clean investment capital. In 2010
the United Nations Framework Convention on Climate Change (UNFCCC) has included
18
OLPs in a list of Clean Development Mechanism (CDM) methods that developed
countries can use to earn certified emission reduction (CER) credits (UNFCCC, 2010) .
These CERs can be traded and sold, and used by industrialized countries to meet a part of
their emission reduction targets under the Kyoto Protocol. “The mechanism stimulates
sustainable development and emission reductions, while giving industrialized countries
some flexibility in how they meet their emission reduction limitation targets” (UNFCCC,
2007). Inclusion of OLPs in the list of accepted CDM methods may result in growth of
the OLP market beyond what would occur without any additional incentives.
In Figure 3, Lighting Africa presents three projected scenarios for the growth of
the SPL market over the next five years. Even the most conservative estimate forecasts a
45% growth in SPL sales, which suggests that the off-grid lighting market, as a whole,
will also experience similar expansion.
19
Figure 3: Solar Portable Light (SPL) market growth scenarios (reproduced from Lighting Africa,
2010c).
Short term exponential growth is expected for the OLP market, but there still exist
several barriers to wide scale use and market penetration. From top to bottom, the OLP
market is hindered by inadequate financial structures. Lighting Africa found that many
manufacturers lack the capital to procure components and produce finished goods before
receiving payment. In the middle, many distributors are stretched thin when they
simultaneously purchase wholesale products and extend credit to dealers. Further down
the line, the consumers also experience financial challenges. Most low-income African
consumers are unable to make lump-sum payments and have limited access to credit. As
a result, good quality OLPs are still out of reach for much of the target population.
20
Current trade and economic policies are also hindering the success of the OLP market.
Many African countries are collecting tariffs and taxes on OLPs that result in higher retail
prices for the consumers. Although some countries are moving to reduce or remove
taxation of OLPs, others continue to assess customs duties and value added taxes that can
add 10% - 30% to the product price (Lighting Africa, 2010d).
1.4 Lighting Africa – Catalyzing Markets for Modern Lighting
“Lighting Africa, a joint IFC and World Bank program, is helping develop
commercial off-grid lighting markets in Sub-Saharan Africa as part of the World
Bank Group‟s wider efforts to improve access to energy. Lighting Africa is
mobilizing the private sector to build sustainable markets to provide safe, affordable,
and modern off-grid lighting to 2.5 million people in Africa by 2012 and to 250
million people by 2030” (Lighting Africa, 2011).
Lighting Africa‟s approach to supporting development of the off-grid lighting
market is divided into five areas: quality assurance, market intelligence, consumer
education, business support, and policy research.
“Lighting Africa lowers market entry barriers of the off-grid lighting market at
every step, from the design of lighting products, to their commercial production and
distribution. The program works with manufacturers of lighting products, distributors,
consumers, financial institutions and governments to build a lasting market for
reliable, practical and affordable lighting products” (Lighting Africa, 2011).
By addressing off-grid lighting at all levels, from individual components and
system design, to regulation, distribution and consumer awareness, Lighting Africa is
working to build a self-sustaining market that can ultimately improve the lives of the
world‟s population that lack access to suitable lighting service.
21
1.5 OLP Quality Assurance
This study is intended to be directly applicable to Lighting Africa‟s quality
assurance strategy, which “supports market development, provides technical advisory
services to quality oriented companies, and protects the interests of low-income
consumers” (Lighting Africa, 2011). As seen in other related industries such as PV
panels and compact fluorescent light bulbs, product testing and minimum performance
standards are needed in order to maintain the integrity of the market.
As previously stated, minimal product quality standards in the emerging OLP
market are leading to market spoilage that is detrimental to consumers and to the outlook
for small-scale off-grid lighting products as a whole. Problems associated with poor
quality, mislabeling, counterfeiting and lack of consumer awareness “can be addressed
through the growth of quality testing and certification programs at the national level…
Well funded and heavily promoted region-wide product quality testing solutions will be
necessary to reduce information asymmetries for consumers and improve the quality of
existing products by providing vital feedback to manufacturers” (Lighting Africa, 2010d).
Mills and Jacobson stress the urgency of establishing a quality assurance framework for
OLPs:
“Given the rising popularity of the LED lighting concept for developing countries,
and the impending launch of major deployment programs, there is a specific urgency
to formalize a product quality and performance testing process, and ensure that the
results reach key audiences. The failure to do so will invite market-spoiling problems
that will ultimately inhibit the penetration of good products and the achievement of
significant energy, economic, and environmental benefits. Indeed, this process may
already have begun” (Mills & Jacobson, 2008).
22
Currently, Lighting Africa is working with OLP market stakeholders to develop a
quality assurance strategy. Whatever the final outcome, performance testing of OLPs
will be a critical piece in any quality assurance program. There are, however, no
internationally accepted test methods or performance standards for OLPs. Standard test
methods exists for some of the individual components (e.g. LEDs, batteries, PV
modules), yet no system level tests or standards have been widely accepted for OLPs
since they are an emerging application of relatively new technologies.
1.5.1 Lighting Africa Quality Test Method (QTM)
Lighting Africa has developed a set of standardized test methods to evaluate the
performance of off-grid lighting products sold in Africa. The primary test method for
product performance verification is the Lighting Africa Quality Test Method (QTM).
“The QTM is designed to be faster and less expensive (in terms of personnel time and test
instrument requirements) than many existing test methods that can be applied to solar and
lighting products” (Lighting Africa, 2011). The QTM is freely available for use by
product manufacturers, government agencies, multi-lateral institutions, bulk-purchasing
agents, non government organizations (NGOs), importers, and others who need to
identify good-quality products or verify compliance with minimum performance levels
(Lighting Africa, 2011).
Lighting Africa is currently supporting OLP manufacturers whose products meet
minimum performance criteria. The QTM is being used to measure key performance
23
metrics and to verify claims made by manufacturers on specification sheets. OLPs that
have proven to be of high quality gain qualification for business, marketing and product
development benefits provided by Lighting Africa. The QTM also serves as the
foundation for the UNFCC CDM methodology for evaluating the impact of substituting
fuel-based lighting with LED lighting systems. Some African governments have also
shown interest in the QTM as a means of enforcing quality control standards on a
country-wide level.
The QTM, therefore, is being crafted with the African OLP market and
infrastructure in mind. Internal regulation of products that enter a country will require
testing centers that verify compliance to standards. Testing bodies in developing
countries are often poorly funded and operate on a shoestring. As such, quality assurance
test methods that are appropriate for use throughout Africa and the developing world
should not require expensive equipment. Nor should the tests require operators with
highly specialized education that may not be available locally. The QTM is also intended
for OLP manufacturers who would like to conduct in-house performance testing for
quality assurance and research and development. The ideal test method is quick and
affordable to conduct, while delivering test results that are useful for analysis of
component and system level performance.
The QTM originates from a report prepared by the Fraunhofer Institute for Solar
Energy Systems (FISE) titled Stand-Alone LED Lighting Systems Quality Screening,
which was developed to evaluate the performance and quality of LED-based off-grid
24
luminaires. Existing standards and test methods for OLP components such as LEDs, PV
modules, batteries and charge controllers serve as a reference for the QTM. These
include specifications from the Global Approval Program for Photovoltaics (PVGAP),
the International Electrotechnical Commission (IEC), and the International Commission
on Illumination (CIE). The QTM is undergoing continuous modifications to correct
shortcomings in the procedure and improve the appropriateness in terms of the Lighting
Africa mission. The current version of the QTM requires a total of 15 product samples,
costs about $6,000 per product, and requires approximately four months for completion.
The QTM is comprised of nine tests that are conducted on six different product samples
(n=6). The QTM consists of the following test procedures:
1. Visual screening of reported performance and general workmanship
2. PV module I-V characterization
3. Battery capacity determination
4. Charge controller characterization
a. Deep discharge protection
b. Overcharge protection
5. Autonomous run time determination
6. Lighting service
a. Luminous flux
b. Light distribution
c. Color characterization
7. Charging behavior characterization
a. Solar charging
25
b. Grid charging
8. Mechanical durability
9. Long-term lumen degradation test (2,000 operational hours)
1.5.2 Lighting Africa Initial Screening Method (ISM)
The Lighting Africa Initial Screening Method (ISM) is a pared down, rapid
version of the QTM intended as a preliminary quality check for OLPs. The ISM is
designed to provide feedback on critical performance criteria in approximately six weeks.
The ISM requires that a single product sample be used for each test (n = 1) and only three
samples are required to test an OLP according to the ISM. The cost for testing a product
according to the ISM is considerably less than the complete QTM. The ISM is useful for
importers, bulk purchasers and government regulators who seek a low-cost test to verify
that a product meets some minimum performance standards. Off-grid lighting
manufacturers that do not have the capacity to conduct advanced research and
development testing in-house can use the ISM for internal performance testing and
quality control. For manufacturers that seek business and technical services from
Lighting Africa, the ISM serves as a low-cost „gateway‟ test to evaluate a product‟s
potential to pass the more rigorous and expensive QTM. The ISM is comprised of the
following tests:
1. Visual screening of reported performance and general workmanship
2. PV module I-V characterization
26
3. Battery capacity determination
4. Autonomous run time determination
5. Lighting service
a. Light distribution
6. Charging behavior characterization
a. Solar charging
b. Grid charging
7. Mechanical durability
8. Long-term lumen degradation test (500 operational hours)
1.6 OLP Systems
To understand the specific testing methodology addressed in this research, one
must first be familiar with off-grid lighting systems and components. In this section,
OLP systems are broken down into four sub-systems: light source (particularly LEDs),
control circuitry (battery charge/discharge and LED driver), energy conversion (PV
modules), and energy storage (rechargeable batteries). The individual system
components are not complex, but integration into a complete system that is inexpensive,
useful, efficient and durable can be complicated and requires well-educated design
choices. “Ideally, the lighting design process results in a solution that balances the user‟s
needs, the economics and environment” (Freyssinier et al., 2009). A conceptual diagram
of a typical OLP system and sub-systems is shown in Figure 4.
27
Figure 4: Conceptual system description of a typical off-grid lighting product (reproduced from
Mills & Jacobson, 2008).
28
1.6.1 Energy Conversion: Photovoltaic Modules
Energy for powering the OLP is often provided by a photovoltaic (PV) module.
Due to the low power draw and high luminous efficacy of LEDs, the daily energy
required to operate most OLPs can be provided by PV modules with peak output less
than 10 watts. Typical OLPs include PV modules that are about 2.5 watts and the size of
a small book (Lighting Africa, 2010d). PV modules made of mono- and polycrystalline
silicon as well as amorphous silicon are commonly used in OLP applications. PV
modules are integrated into the body of the OLP or connected remotely, according to the
form and function of the product.
The largest costs in today‟s SPLs are concentrated in the solar panel, which often
accounts for well over 30% of a typical solar lantern or torch component costs (Lighting
Africa, 2010d). The good news for the future of off-grid power systems is that the cost of
PV modules (on a dollar per peak watt basis) has been rapidly declining. The recent
trend and short term forecast for crystalline and amorphous silicon PV panel prices are
shown in Figure 5. Continued improvement in PV panel efficiency and further cost
reductions are expected in the coming years. As a result, the price of high quality OLPs
will become more affordable for low-income consumers.
29
Figure 5: Off-grid lighting product solar panel prices are expected to continue rapid cost decline
driven by crystalline PV price declines along with a shift to amorphous thin-film technology
(reproduced from Lighting Africa, 2010c).
1.6.2 Batteries
OLPs rely on rechargeable batteries to store energy from the PV module and to
power lights and other product functions. The batteries commonly used in OLP products
are of four chemistry types: sealed lead acid (SLA), nickel cadmium (NiCd), nickel
metal hydride (NiMH), and lithium ion (Li-ion). Most batteries used in OLPs are widely
available commercially. Each battery chemistry offers a unique combination of
attributes, including cost, physical size and weight, storage capacity, lifecycle, and
toxicity, to name a few. Product designers, therefore, have access to a variety of energy
storage options that can be selected according to the specific system demands. The
availability of these common battery types also allows for replacement by the consumer.
30
Currently, NiMH batteries account for over half of the batteries found in OLPs, but
Lighting Africa research suggests that Li-ion batteries will gain an 80% market share by
2020 (Lighting Africa, 2010d).
1.6.3 Control Circuitry
Electronic control circuitry is essentially the „brains‟ of the OLP that connects all
of the individual components, forming a functional system. Properly designed control
circuitry efficiently regulates the battery charging and discharging, drives the light source
at appropriate (and often adjustable) levels of current and voltage, allows for other system
functions like mobile phone charging, and protects the OLP components from electrical
damage. Additionally, portable lighting products are subjected to a range of environments
and operating conditions that require the integrated circuitry to be physically robust. In
order to create an OLP that is appropriate for the African off-grid market, the control
circuitry must accomplish all of the aforementioned functions while maintaining low
hardware and manufacturing costs.
The OLP control circuitry is of particular interest to the research conducted in this
thesis since it is directly tied to the lumen maintenance and overall lifetime of a lighting
product. Experience with testing a broad range of high and low quality products has
shown that the circuit design is often the root of poor performance and device failure.
Especially in the lowest cost OLPs, simply designed drive circuitry has been witnessed to
push too much current through the LEDs and ineffectively regulate the battery state of
31
charge. If the control circuit, itself, does not first experience catastrophic failure, the
battery and LEDs will soon fail to operate properly. Poorly controlled batteries are prone
to drastically reduced storage capacity and over-driven LEDs will rapidly become so dim
that the OLP is essentially unusable.
1.6.4 Light Emitting Diodes (LEDs)
The Illuminating Engineering Society of North America (IESNA) has issued TM-
16: Technical Memorandum on Light Emitting Diode (LED) Sources and Systems, which
is one of the foremost technical references on LEDs. The report‟s general description of
LEDs is useful here as a working definition:
“LEDs are solid-state semiconductor devices that convert electrical energy into
visible light. When certain elements are combined in specific configurations and
electrical current is passed through them, photons (light) and heat are produced. The
heart of LEDs, often called a „die‟ or „chip,‟ is composed of two semiconductor layers
– an n-type layer that provides electrons and a p-type layer that provides holes for the
electrons to fall into. The actual junction of the layers (called the p-n junction) is
where electrons and holes are injected into an active region. When the electrons and
holes recombine, photons (light) are created. The photons are emitted in a narrow
spectrum around the energy band gap of the semiconductor material, corresponding to
visible and near-UV wavelengths” (IESNA, 2005).
The symbol for an LED used in circuit diagrams is shown in Figure 6. When
sufficient current flows across the p-n junction of an LED, visible light and heat is
produced. Figure 7 shows the basic parts of a through-hole type LED.
32
Figure 6: Electrical model of a light emitting diode (LED) (reproduced from IESNA, 2005).
Figure 7: Components of a typical through-hole type LED package. The epoxy encapsulant, wire
bond, reflective cavity, semiconductor die and leadframe are common to all types of LED packages
(reproduced from Wikipedia, 2009).
The first practical LED, invented in 1962, emitted light in the red portion of the
visible spectrum. Over the next two decades, the technology had developed such that
LEDs could emit other colors of light. The subsequent invention of two semiconductor
33
materials used in LEDs, Aluminum gallium indium phosphide (AlGaInP) and Indium
gallium nitride (InGaN), finally “enabled LEDs to become a readily available commercial
product” (IESNA, 2005). LEDs made of AlGaInP and InGaN have a much higher light
output than the earlier LEDs. “In addition, these materials allowed, for the first time,
LEDs with peak wavelengths at any part of the visible spectrum to be made” (Bullough,
2003). AlGaInP and InGan LEDs are coated with phosphors that convert the emitted
light into white light, much like the phosphors that are used in fluorescent tubes.
Commonly available LEDs are now capable of generating white light that is both „warm‟,
indicating a yellowish appearance, and „cool‟, which appears bluish in color.
LEDs are also experiencing rapid improvement in luminous efficacy, which is
defined as “the luminous flux (lumens) produced by the system divided by the system
power input (Watts) and is expressed lm/W” (IESNA, 2005). The U.S. Department of
Energy (DOE) has been tracking the luminous efficacy of LEDs, and the trend suggests
that warm and cool LEDs will reach 160 lm/W and 220 lm/W by the year 2020,
respectively (Welsh, 2009). The DOE‟s forecast of LED luminous efficacy is shown in
Figure 8. In terms of luminous efficacy, the outlook for LEDs is quite promising.
Conventional light sources like fluorescent and high intensity discharge (HID) lamps
currently have luminous efficacies slightly above 100 lm/W, with little expected
improvement over the coming decade. Compact fluorescent lamps, which are perhaps a
more direct competitor with LEDs in the short term, generally have luminous efficacies
on the order of 40 – 60 lm/W. With energy efficiency becoming a key design criterion, it
is likely that LEDs will replace conventional light sources in many applications.
34
Figure 8: Trends and projections for luminous efficacy of commercially available cool and warm
white LEDs. The line labeled as “2008 MYPP Comm Warm White” is the U.S. Department of
Energy‟s multi-year program plan projection for the increase in luminous efficacy of commercially
available, warm white LEDs (reproduced from Welsh, 2009).
From an economic perspective, LEDs still lag behind conventional light sources.
In 2009, the DOE found that on a normalized light output basis, LEDs are more than 430
times the cost of incandescent light bulbs and more than 50 times the cost of a CFL. Yet,
cost and performance trends suggest that over the next several years, LED light sources
are projected to become competitive on a first-cost basis (U.S. Dept. of Energy, 2010).
While LEDs may still be insufficient for several illumination applications, the
current cost, performance and unique characteristics of LEDs have already proven to be
appropriate for use in OLPs. LEDs are solid-state devices, which means that there are no
35
filaments or moving parts that are prone to mechanical failure. The size and versatility of
LEDs have also proven to be extremely useful in OLP applications. LEDs come in a
range of sizes from tenths of millimeters to packages more than 1mm2. The reflective
cavity and epoxy encapsulant in LED packages can be used to create different light
distribution patterns. As such, LEDs can be used individually or combined in arrays to
provide light in a wide variety of light output, color and spatial distributions. The fact
that LEDs are direct current, low voltage devices allows them to be easily and efficiently
integrated into photovoltaic or other DC systems (Freyssinier et al., 2009).
1.6.5 Lumen Maintenance of LEDs
One of the important benefits of using LEDs in OLPs and other lighting devices is
the potential for service life greater than 50,000 hours, more than nearly any other light
source. Unlike conventional light sources, LEDs do not tend to fail catastrophically.
Instead, they experience an irreversible decrease in light output over time, called lumen
depreciation. The ability of an LED to emit a constant level of light over its operational
life is referred to as lumen maintenance, which is the inverse of lumen depreciation. In
their approved method for measuring lumen maintenance of LED light sources, denoted
as LM-80, the Illuminating Engineering Society (IES) defines lumen maintenance as “the
luminous flux output remaining (typically expressed as a percentage of the maximum
output) at any selected elapsed operating time” (IES, 2008). The Alliance for Solid-State
Illumination Systems and Technologies (ASSIST) recommends that LED life for general
36
illumination be defined by the time it takes for the light output to reach 70% of its initial
light level, denoted by L70 (Narendran et al., 2007). A 30% decrease in the luminous
flux emitted by an LED has been determined to be close to the threshold at which the
human eye can detect a reduction in light output. An LED product that has reached the
L70 light level can be considered a failed unit even though it still produces light. The
L70 level has become an accepted lifetime level for LED systems and is used by Lighting
Africa as the standard LED lifetime in OLPs (Lighting Africa, 2010b).
The non-reversible decrease of luminous flux during extended use is primarily
caused by heat generated at the LED junction. “LEDs are notoriously more sensitive to
temperature effects than any other light source” (Freyssinier et al., 2009). This is due to
the fact that LEDs do not emit heat as infrared radiation like other light sources. As a
result, the heat must be removed from the device by conduction or convection. Without
adequate heat sinking or ventilation, the LED junction temperature will rise, resulting in
lower light output. While the effects of short-term exposure to high temperatures can be
reversed, continuous high temperature operation will cause permanent reduction in light
output (U.S. Dept. of Energy, 2006).
In addition to insufficient heat sinking, excessive electrical current through the
LED also results in elevated junction temperatures. With increasing power there is
increased thermal load and more heat to dissipate. This phenomenon is referred to as
thermal runaway (Cooper, 2007). Other causes of LED lumen depreciation include poor
37
LED chip quality, encapsulant degradation, and LED bond wire electric resistance
(Lighting Africa, 2010b).
Testing low quality off-grid lighting products at SERC has shown that many of
the products available to consumers in Africa exhibit rapid lumen depreciation (Mink et
al., 2010). Ineffective heat sinking and overdriving the LEDs are common design flaws
in these devices. Rapid lumen depreciation of off-grid LED lights is a major concern
when attempting to protect the interests of consumers and the integrity of the OLP
market. Products that provide high forward current through the LEDs and poor heat
dissipation can greatly mislead the purchasers. When a product is just off the shelf, the
consumer is impressed by the brightness achieved by overdriven LEDs. Yet, the users
are disappointed shortly thereafter when the light is drastically dimmer, perhaps even
unusable. Ultimately, the consumer loses money and OLP market spoilage is propagated.
1.6.6 Lumen Maintenance Testing
An important criterion for assessing the quality of an off-grid lighting system is
the product lifetime. A well-designed product provides useful lighting service for a
length of time that reduces the operating cost to a level lower than fuel-based alternatives.
Modern off-grid lighting technologies must be competitive on the basis of cost-per-time
of lighting service if they are to be adopted by low-income consumers. Unfortunately,
many products exhibit such rapid lumen depreciation that the potential economic savings
are never achieved.
38
With this in mind, lumen maintenance testing of OLPs is an important part of the
Lighting Africa quality assurance strategy. The QTM includes an OLP-specific method
for measuring lumen maintenance that is derived from existing standards and
internationally accepted methods. The test method established in LM-80-08 by the IES
serves as the primary methodological reference for determining the lumen maintenance
of LED light sources.
LM-80 specifies that luminous flux is to be measured “in conformance with the
appropriate laboratory method for the LED light source under test.” To comply with
LM-80, the LED must be operated “for at least 6,000 hours with data collection at a
minimum of 1,000 hours”, resulting in a minimum of six measurements over the course
of the test. These measurements are typically conducted with an integrating sphere-
photometer, as described by the CIE technical report on the measurement of luminous
flux (CIE 84-1989). LM-80 states that the LED is to be driven at a constant current that
is specified by the LED manufacturer, and must be regulated to within +/-3% of the rated
value over the testing period. The ambient air temperature shall be maintained at 25oC
+/-2oC and airflow must be minimized in order to reduce the effects of convective heat
transfer away from the LED package. A lumen maintenance test report must include all
of the operating conditions and the percent change in initial luminous flux at each
measurement interval.
LM-80 has proven to be an accurate method for measuring the change in LED
luminous flux over time, but it can be inappropriate for widespread use in OLP quality
39
assurance testing. Slight alterations to LM-80 have been integrated into the Long-Term
Lumen Degradation Test in Lighting Africa‟s QTM and ISM in order to reduce the time,
expense, and complexity of OLP lifetime testing.
The most significant deviation from LM-80 is the means by which OLP light
output is measured. The QTM and ISM specify that, in addition to an integrating sphere-
photometer system, illuminance measuring devices can be used to measure the relative
change in light output over time (Lighting Africa, 2010c). Since illuminance (lux, or
lm/m2) is derived from luminous flux (lm), relative change in illuminance can serve as a
proxy for the change in luminous flux.
“A measurement of illuminance in a fixed geometry (such as a dark room or
isolated box) is always directly proportional in a linear fashion to the luminous flux of
a lamp. Therefore, fixed-geometry measurements of illuminance can be used in place
of luminous flux measurements for this test, which relies on relative light output to
indicate the change in useful power emitted by a light source over time” (Lighting
Africa, 2010c).
This directly proportional relationship between lux and lumens allows lumen
maintenance measurements to be made with much simpler and inexpensive equipment.
Detailed descriptions of the integrating sphere and the alternative illuminance measuring
devices are in Section 1.8.
Lighting Africa‟s Long-Term Lumen Degradation Test also includes a few other
deviations from the LM-80 method. Firstly, the QTM and ISM state that lumen
maintenance measurements are to be conducted on OLPs over a period of 2,000 and 500
hours, respectively. The abbreviated lumen maintenance testing period is intended to
shorten the overall product testing time, thereby reducing the cost of testing. The
40
rationale for a 2,000 hour test in the QTM is based on the expected lifetime and daily use
of typical OLPs. The 500 hour test in the ISM is intended to identify products that
experience extremely fast lumen depreciation before proceeding to the QTM.
Another divergence of the QTM from the LM-80 procedure is how the OLP is
powered during the lumen maintenance test. Since OLPs are battery powered, the light
source in a product is driven at different levels according to the battery state of charge
and the particular behavior of the control circuitry. The constant current specified in LM-
80, therefore, does not apply to OLPs. Instead, the QTM and ISM require that the OLP is
driven at the product‟s nominal battery voltage.
Finally, the Lighting Africa Long-Term Lumen Degradation Test requires more
frequent measurement intervals than LM-80. With a relatively short 2,000 hour operating
period, the light output measurements in the QTM must be made at least every week in
order to effectively track the change in luminous flux. The 500 hour lumen maintenance
test in the ISM also requires frequent measurements to record the trend in OLP light
output.
Now that the OLP components have been described and lumen maintenance
testing of LEDs has been outlined, it is important to understand the theory behind light
measuring practices. The following sections delve into the science of photometry and the
methods for measuring light.
41
1.7 Photometry
Visible light describes the part of the electromagnetic spectrum that can be sensed
by the human eye. From a physiological perspective, light waves are those having a
periodicity of such value that when they are received by the retina of the eye they
produce the sensation of vision in the brain (Barrows, 1912). Humans are able to see
light with wavelengths between 380 nm and 770 nm. The location of the visible
wavelengths within the electromagnetic spectrum is shown in Figure 9. Note that the
human eye perceives light with smaller wavelengths as violet in color and larger
wavelengths are perceived as red.
Figure 9: Electromagnetic spectrum, including the range of visible light wavelengths detectable by
the human eye (reproduced from Irvine, 2010).
42
Photometry is the science of the measurement of light in terms of its perceived
brightness to the human eye (Bass, 1995). In fact, photometry is the only system of
physical measurement that is based entirely on human perception. The spectral response
of the human eye, however, varies from person to person as well as between well-lit and
low light conditions. Our vision in well-lit conditions, or photopic vision, is most
sensitive to a wavelength of 555 nm (green). Under low light conditions, our perception
of light is called scotopic vision, and our eyes are most sensitive to wavelengths around
498 nm (green-blue). In 1924, the Commission Internationale de l‟Eclairage (CIE)
recorded the spectral response of 52 experienced observers. The data resulted in a
standard luminosity curve, or V-lambda (V) function, commonly called the photopic
response of the standard observer (Labsphere, 2008a). The typical photopic and scotopic
response of the human eye are shown in Figure 10.
43
Figure 10: V-lambda curve describing the sensitivity of the „standard observer‟ (i.e. typical human
vision) to different wavelengths in the visible spectrum, according to scotopic (low light) and photopic
(well-lit) conditions (reproduced from Electro Optical Industries, Inc., 2010).
1.7.1 Luminous Flux
Luminous flux is a measure of the power of visible light and is expressed in terms
of lumens (lm). Luminous flux () is derived from radiant flux (e), which is the energy
per unit time (watts) that is radiated from a source with wavelengths from 0.01m to
1,000 m. Luminous flux is determined by evaluating radiant flux according to its action
upon the CIE standard photometric observer. For photopic vision, luminous flux is
calculated according to Equation 1.
44
Equation 1: Luminous flux is calculated by integrating the spectral distribution of a light source‟s
radiant flux over the spectral luminosity function specified by the CIE curve (CIE, 1996).
where:
Luminous flux (lumens).
= Lumens per watt conversion factor for the CIE function (683 lm/W).
= Spectral distribution of the radiant flux (lm/nm).
= Spectral luminous efficiency of the standard observer.
1.7.2 Luminous Intensity
Luminous intensity (I) of a light source is a measure of visible power emitted per
solid angle, expressed in candela, which is equal to lumens per steradian (lm/sr). A
steradian is defined as the solid angle, which, having its vertex at the center of a sphere,
cuts off a spherical surface area equal to the square of the radius of the sphere (Ryer,
1997). A sphere contains 4 steradians.
1.7.3 Illuminance
Illuminance is a measure of the luminous flux incident on a surface per unit area.
Illuminance at a point of a surface (EV) is the quotient of the luminous flux incident
on an element of the surface containing the point, by the area dA of that element (CIE,
45
1996). Illuminance is measured in units of lux (lx), which is equal to lm/m2
, and is
calculated by Equation 2.
Equation 2: Illuminance is a measure of the total amount of visible light on a surface (CIE, 1996).
where:
Illuminance at a point of a surface (lux).
= Luminous flux incident on an element of the surface containing the point (lumen).
= Area of the element of the surface (m2).
1.7.4 Determining Luminous Flux of a Light Source
According to CIE 84-1989, the internationally recognized standard for measuring
luminous flux, the luminous flux of a light source can be calculated or measured by the
following methods:
Calculation from the luminous intensity distribution
Calculation from the illuminance distribution
Measurement with a sphere photometer by photometric or spectral measurements
Measurement with a box photometer
Relative measurements via illuminance, luminous intensity or luminance (CIE,
1996)
46
This study follows the sphere photometer (integrating sphere) method to measure
the luminous flux of light sources. The illuminance distribution and box photometer
methods were also referenced in this research to evaluate light distribution patterns of the
tested products and to measure the relative change in product light output, respectively.
1.8 Light Measuring Devices
The research described in this thesis is based on the previously outlined
photometric principles and their application in a laboratory setting. Several light
measuring devices, ranging from simple to complex, were used to quantify the light
output of the OLPs and evaluate the accuracy of the low-cost test methods in question.
The NLTC made available devices such as a spectroradiometer, a goniophotometer, and
an integrating sphere for use in this research. Less complex devices like an illuminance
meter as well as the tube- and box-photometers were also required. The following
sections describe the light measuring devices used in this research.
1.8.1 Spectroradiometer
A spectroradiometer is a device that measures light power as a function of
wavelength. The device consists of a detector coupled to a spectral separation device
such as a diffraction grating monochromator or a Fourier transform interferometer
(Labsphere, 2008b). In simplified terms, a spectroradiometer disperses the light
47
spectrum, then incrementally scans each wavelength, and measures the intensity of each
narrow wavelength band. The device then weighs and integrates the light power
distribution according to the spectral response of the human eye (V) in order calculate
the luminous flux of a light source.
1.8.2 Illuminance meter
An illuminance meter, often referred to as a lux meter, uses a photocell to convert
incident light energy into electrical current. The amount of current output by the
photocell is directly dependent on the amount of light that strikes the photocell. The
meter then converts the electrical signal to units of lux according to the photopic V()
spectral sensitivity curve established by CIE.
1.8.3 Goniophotometer
A goniophotometer is a device that measures the directional light distribution
characteristics of light sources, luminaires, media and surfaces (CIE, 1996). A
goniophotometer consists of a goniometer and an illuminance meter. A goniometer is an
instrument that rotates an object about a fixed axis in precise angular increments.
In practice, a light source is placed in the center of the device and the goniometer
arm with an attached mirror rotates 360 degrees around the light source in a single plane.
An illuminance meter located at a fixed distance perpendicular from the plane of
48
goniometer rotation records the illuminance at each angular step of the arm. The
goniophotometer repeats the illuminance measurements on multiple planes. By
combining the illuminance measurements for each plane, a spherical „map‟ of the
source‟s light distribution can be created. The goniophotometer can be calibrated using a
light source of known luminous flux to calculate the luminous flux of the tested lamp.
1.8.4 Integrating Sphere
An integrating sphere, also known as an Ulbricht sphere, is a hollow sphere
whose internal surface is a diffuse reflector that spatially integrates radiant flux
(Labsphere, 2008a). The integrating sphere is a photometric device used for several
common photometric measurements, including radiant and luminous flux, laser power,
reflectance and transmittance of materials. The sphere can also be used as a large area
diffuse light source. This study focuses on using an integrating sphere in combination
with a spectroradiometer to measure the luminous flux of a light source.
An integrating sphere is so named due to the behavior of light within the hollow
cavity. The highly diffuse reflectivity of the sphere‟s interior white coating results in
uniform scattering of light. An ideal interior surface is Lambertian, meaning that it
exhibits 100% reflectance and completely uniform angular spreading of the light energy
on the first bounce. When an ideal Lambertian surface is combined with a spherical
enclosure, the geometry of the sphere ensures that every point within a sphere receives
the same intensity of light as every other part of the sphere at the first bounce
49
(SphereOptics, 2007). Typical integrating spheres are coated with barium sulfate-based
optical paints with reflectance near 0.8, as recommended by CIE-84.
When a light source is placed in the center of an ideal integrating sphere, the
illuminance on a unit area of the interior surface is equal to the illuminance on all other
unit areas within the sphere. The luminous flux of the light source, therefore, can be
calculated by integrating over the entire sphere surface. By definition, the luminous flux
can be derived from the distribution of illuminance over a closed surface around the light
source using the relation in Equation 3.
Equation 3: The luminous flux of a light source in an ideal integrating sphere is calculated by
integrating the illuminance measured on a discrete surface over the entire surface area of the sphere
(CIE, 1996).
where:
Luminous flux (lm).
A = Area of closed surface surrounding the light source.
E = Illuminance at a point on the closed surface.
In reality, however, an integrating sphere exhibits non-ideal behavior since the
interior coating is not completely Lambertian, the sphere surface contains some irregular
geometry, and the light source itself interacts with the reflection of light off the sphere
walls. As discussed below, the accurate measurement of luminous flux also requires that
50
two baffles and a second „auxiliary‟ lamp be placed in the sphere. A diagram of the basic
integrating sphere components is shown in Figure 11.
Figure 11: Lamp measurement sphere using a detector mounted directly at the view port
(reproduced from Labsphere, 2008a)
The spectroradiometer labeled as “Detector” in the Figure 11 receives light
through a small, light diffusing viewing port that is set flush with the interior surface of
the sphere. Notice that a baffle is placed between the light source and the viewing port.
This is to prevent the detector from being directly illuminated by the light source and to
prevent the detector from directly viewing a part of the sphere wall that is directly
illuminated. Either of these situations introduces a false response since the luminous flux
of the source is directly proportional to the illumination of the sphere wall (Labsphere,
2008b). The baffle is coated with the same paint as the sphere and it has a size and
placement that only allow light to enter the viewing port after two reflections from the
sphere wall.
51
With additional surface irregularity introduced by the viewing port and an
additional obstacle created by the baffle, the sphere can no longer determine the luminous
flux of a light source according to Equation 3. The luminous flux of a light source can,
however, be measured in an integrating sphere by a comparison with a luminous flux
standard lamp (CIE, 1996). A standard lamp is a reference light source that produces a
known luminous flux when driven at a specified voltage and current. Standard lamps are
calibrated at national standardizing laboratories according to National Institute of
Standards and Technology (NIST) total spectral radiant flux measurements. These „NIST
traceable‟ standard lamps are necessary for accurate measurement of a test lamp‟s
luminous flux in an integrating sphere. Incandescent lamps are generally used for lamp
standards because of their inherently good stability and convenience in handling. The
total uncertainty in the assigned values of total luminous flux for an incandescent lamp
calibrated at NIST ranges from 1.4% to 1.8% (Labsphere, 2008a).
The luminous flux of a light source is determined by placing the test lamp and the
standard lamp successively at the same location in the integrating sphere (CIE, 1996).
The luminous flux of the test lamp is calculated from a simple ratio of the test lamp
illuminance measured in the sphere to the standard lamp illuminance measured in the
sphere, multiplied by the NIST traceable lumen output of the standard lamp. This
relationship is calculated according to Equation 4.
52
Equation 4: Since the luminous flux of the standard lamp is known, the luminous flux of the test
lamp can be calculated according to a ratio of measured illuminance multiplied by the lumen output
of the standard lamp (Labsphere, 2008a).
where:
Luminous flux of the test lamp (lm).
N = Luminous flux of standard lamp (lm).
Eind = Indirect illuminance of the luminous flux from the test lamp (lx).
Eind, N = Indirect illuminance of the luminous flux N from the standard lamp (lx).
The calculation of luminous flux using Equation 4 is only valid when the test
lamp has the same size, shape and color as the standard lamp. Physical dissimilarities
between the test and standard lamp result in different „self absorption‟ responses within
the integrating sphere, which causes measurement error. An auxiliary lamp and an
associated baffle, shown in Figure 11, are used to correct for the self absorption of the
standard and test lamps. “The auxiliary lamp remains inside the integrating sphere at all
times. It is usually mounted diametrically opposite the detector port and baffled from
direct view and direct illumination of lamps mounted at the sphere center” (Labsphere,
2008a).
Correction for self absorption is accomplished by placing each unilluminated
lamp in the integrating sphere and operating the auxiliary lamp. The illuminance
measured by the detector is recorded with each lamp in the sphere and the self
absorption-corrected test lamp luminous flux is given by Equation 5.
53
Equation 5: Self absorption correction for the luminous flux of a light source is the ratio of
measured lux when the auxiliary lamp is illuminating the standard lamp to the lux measured when
the test lamp is in the sphere (Labsphere, 2008b).
where:
Eaux, s = Indirect illuminance measured by the detector for the auxiliary lamp with the
unilluminated standard lamp in the sphere (lx).
Eaux, t = Indirect illuminance measured by the detector for the auxiliary lamp with the
unilluminated test lamp in the sphere (lx).
Finally, if the standard and test lamps have different spatial luminous flux
distributions, the test lamp luminous flux may need to be corrected to account for
dissimilar responses in the integrating sphere. This correction is necessary when the
interior sphere surface exhibits high levels of non-uniformity and when a highly
directional test lamp is compared to a uniformly distributed standard lamp.
Light distribution mismatch is corrected through characterization of the spatial
light distribution of both lamps and measurement of the average sphere reflectance over
the area illuminated by each light source. The luminous flux of the test lamp calculated
in Equation 5 is corrected for light distribution mismatch by multiplying by the following
ratio in Equation 6:
Equation 6: Light distribution mismatch correction is used to adjust the measured luminous flux of
the test lamp when the standard lamp has a different spatial light distribution pattern.
54
where:
Average reflectance of the sphere surface over area that is encompassed by the
full width half maximum (FWHM) angle of the standard lamp.
Average reflectance of the sphere surface over area that is encompassed by the
full width half maximum (FWHM) angle of the test lamp.
Refer to the Sections 2.2.1 and 2.2.2 for a detailed explanation of the methods used in this
study to determine the terms in Equation 6.
1.8.5 Box-Photometer
Luminous flux is usually measured with an integrating sphere in accordance with
CIE 84. However, if an integrating sphere is not available, a self-made device, referred
to as a box-photometer, can be used for measuring luminous flux (Lighting Africa,
2010c). A box-photometer is an integrating photometer employing an arbitrarily shaped,
hollow box or cavity that can be used to compare the luminous flux of light sources of the
same type (CIE, 1996). An interior view and a three dimensional rendering of a box-
photometer are shown in Figure 12.
55
Figure 12: Box-photometer (left: Interior view, right: 3-D view) (reproduced from Lighting Africa,
2009).
When comparing a box-photometer to an integrating sphere, one must understand
the difference in behavior of light within the cavity. Unlike an integrating sphere, the
light striking a discrete area on the interior box surface is not necessarily equal to other
areas of the interior surface. This non-uniformity is due to irregularities from imprecise
construction, angular intersections of the box walls and inconsistency in the surface
coating. As a result, a box-photometer is much more sensitive than an integrating sphere
to changes in the location and orientation of the light source within the cavity, as well as
mismatches between the size and light distribution of the standard lamp and device under
test (DuT). A luminous flux measurement with a box-photometer only presents a direct
relationship between the luminous flux of the light source and indirect illuminance at an
arbitrary point at the inside surface of the box, provided that the reference light source
and light source to be measured have the same spatial luminous intensity distribution, the
same spectral distribution, and same dimensions (CIE, 1996). The use of box-
photometers to determine the luminous flux of light sources has been previously
56
investigated, but “results with respect to accuracy and theoretical correctness seem to
favor the globe photometer [integrating sphere]. Its only advantage appears to be in the
mechanical simplicity of its construction” (Barrows, 1912).
The use of a box-photometer for measuring the luminous flux of a light source
was investigated in depth by Dr. Gerhard Krenzke in 1965. Krenzke determined the
optimal geometry and dimensions of a box-photometer for measurement accuracy in the
device. The optimal measuring configuration for a box-photometer is shown in Figure
13, where:
L = Light source
F = Measuring window
S = Measuring window shade
H = Auxiliary lamp
SH = Auxiliary lamp shade
57
Figure 13: Optimal measuring configuration for a box-photometer (reproduced from Krenzke,
1965).
Although previous studies have shown that a properly constructed and calibrated
box-photometer can be used to accurately measure the luminous flux of a light source,
box-photometers are not commonly employed in modern photometric laboratories. In
practice, box-photometers can be much more difficult and time consuming to calibrate
than integrating spheres. Modern lighting laboratories generally rely on integrating
spheres to make lumen measurements on account of the ease of use, measurement
accuracy, and minimal impact of spatial irregularities. The box-photometer, however, is
useful and convenient for measuring the relative change in light output of a light source.
Relative light output measurements with the box-photometer do not require DuT-specific
58
calibration to deliver quick and accurate results. The box-photometer used in this study
was used solely for determining the relative change in light output. The method for
measuring the change in light output with the box-photometer is described in greater
depth in Section 2.3.9.
1.8.6 Tube-Photometer
A tube-photometer is a device used to measure the relative change in illuminance
of a light source over time. The apparatus consists of tube with a cap at one end. The
end cap fits snugly on the tube such that it holds the illuminance meter sensor in a fixed
position and restricts stray light from entering the tube. Light emitted by a DuT is
directed into the open end of the tube and the illuminance incident on the sensor head is
measured by the lux meter. A diagram of the tube-photometer is shown in Figure 14.
Figure 14: Line drawing of a tube-photometer, indicating the basic device components.
Unlike the integrating sphere and box-photometer, the luminous flux of a light
source cannot be determined by the tube-photometer. The tube-photometer is used solely
59
for evaluating the lumen depreciation characteristics of a light source. By placing the
DuT flush with the open end of the tube, the orientation and distance of the light source
from the sensor head can be replicated for each illuminance reading taken throughout the
lumen maintenance test. As long as the same orientation between the light source and
sensor is maintained for each reading, an accurate measurement of relative change in
luminous flux can be achieved.
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2 MATERIALS AND METHODS
An integrating sphere, a box-photometer, and a tube-photometer were used to
conduct parallel measurements over a range of light output levels from four different
OLPs. The test procedure followed in this study, herein referred to as „Simulated Lumen
Maintenance Test,‟ was conducted in order to compare the measurement accuracy of the
tube- and box-photometers for varying magnitudes of light output, spatial light
distribution patterns, and OLP physical characteristics.
2.1 Materials
Equipment for the Simulated Lumen Maintenance Test comprises of four OLPs
that are driven by a benchtop power supply and four light measurement apparatuses: a
goniophotometer, an integrating sphere, a tube-photometer, and a box-photometer. A
complete list describing specifications of the testing devices as well as additional
equipment associated with each device is included in Appendix L. The following
sections discuss the selection and characteristics of materials used in this research.
2.1.1 Devices under Test (DuTs)
Four different OLPs were used as DuTs for testing the box- and tube-
photometers. The lights were selected from several LED products that had been procured
by random market sampling. The lighting devices used in this research were selected
61
according to specific performance characteristics that represent the diversity of OLPs
currently on the market. The first criterion for choosing which products to use for the
research was long lumen maintenance. Stability of the light source is necessary for
comparison of the test methods. Secondly, the products were selected according to light
distribution characteristics. One product has the form of a lantern and emits relatively
uniform light in 360o. The other three products exhibit varying degrees of directional
light distributions that are less than 180o. Finally, the chosen products represent a range
of form factors and luminous flux. Table 1 gives relevant specifications of the four DuTs
used in the research. Photos of the lighting products are in Appendix A and additional
descriptions of the light distribution patterns are in Section 2.2.2.
62
Table 1: Specifications of Devices under Test (DuTs) used in the Simulated Lumen Maintenance
Test.
SAMPLE NAME
FORM FACTOR &
LED TYPE
NOMINAL BATTERY VOLTAGE
(V)
APPROX. NOMINAL LED DRIVE CURRENT
(mA)
APPROX. NOMINAL
LUMINOUS FLUX (lm)
Aishwarya Ambient lantern Through-hole array
6 121 62
Firefly Desktop tasklight Through-hole array
3.6 104 25
Kiran Ambient lantern Single Surface mount
3.6 70 15
Solux Flashlight / Ambient Single Surface mount
3.6 288 71
2.1.2 LED Driver
A simple LED driver circuit was created to provide an adjustable and precise
power source for the DuTs. The LED driver is a critical element in the test procedure
since a lamp‟s light output has a strong dependence on the lamp drive parameters;
accurate and stable electronics are vital to a good photometry system (Labsphere, 2008a).
A precision bench top power supply was used to drive the LEDs at constant current. The
positive and negative leads of the power supply were connected to the DuTs by paired
conductor wire for ease of transfer between the light measuring devices. A simple
current shunt circuit, shown schematically in Figure 15, was used to measure the current
63
flowing through the DuT LEDs. A high precision voltmeter measured the voltage at the
resistor. The current through the resistor is calculated using Ohm‟s law (I = V/R). Since
the DuT and the resistor are connected in series, the current through the resistor is equal
to the current through the DuT LEDs. Specifications of the LED driver circuit elements
and voltmeters are available in Appendix L.
Figure 15: Current shunt circuit used to measure current through the Device under Test (DuT)
LEDs.
2.1.3 Box-Photometer
Much of the following description of the box-photometer used in this study
originates from Section 3.2 of the most recent revision of the QTM available for
download on the Lighting Africa website (Lighting Africa, 2011). Results from this
thesis research as well as the author‟s experience constructing, using and training
technicians to use box-photometer have been integrated into the “Photometer Box”
section of the QTM.
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The box-photometer is designed to be simple and economical to produce. These
attributes are essential for light testing centers in locations that do not have access to
expensive photometric equipment or advanced manufacturing facilities. The box-
photometer used in this study is constructed of basic materials that are generally available
in most countries. Due to their availability, relatively low cost and ease of manufacture,
the materials specified in the plans are considered appropriate for building a photometer
box. Functionally similar materials may be used in place of the recommended materials,
according to local price and availability.
The box is built from plywood, but other strong wood or timber materials can also
be used. A thickness of at least 2.5 cm is recommended to ensure clean processing. On
grounds of cost and procurement difficulty, a highly reflective special coating (which is
normally used for integrating spheres) was not used. Instead, the inner surfaces were
painted with white emulsion paint. Multiple coats of paint (5 or more) improve the
uniformity and reflection of the walls. The finished interior surface is intended to reflect
light as diffusely and homogeneously as possible. Care was taken to apply the paint such
that the surface texture is smooth. Since the box-photometer was not to be used for
luminous flux measurements, the auxiliary light and associated baffle were omitted from
the device used in this study. The baffle located in front of the photometer sensor port is
built of 0.5cm-thick plywood and threaded metal rods with a 5 mm diameter. The rods
and baffles were also painted with white emulsion paint. A thermocouple was mounted
to one of the baffle rods to monitor the temperature inside the box-photometer during
testing. An Extech 401036 datalogging photometer sensor measured light in the box
65
through a port made of PVC pipe. The test stand in the center of the box was custom
made of a machined aluminum base and a threaded metal rod welded to a square piece of
sheet metal with approximate dimensions of 10cm x 10cm. Refer to Appendix L for a
list of the box-photometer components, and Appendix J for detailed plans and
construction directions.
2.1.4 Tube-Photometer
Much of the following description of the tube-photometer used in this study
comes from section 3.3 of the most recent revision of the QTM available for download on
the Lighting Africa website (Lighting Africa, 2011). The author wrote the “Photometer
Tube” section of the QTM according to his experience constructing, using and
researching the tube-photometer.
The tube-photometer is a simple, hand-made device for taking measurements of
relative luminous flux. Like the box-photometer, the tube- photometer also consists of
low-cost materials that are readily available in most countries. A photo of the tube-
photometer used in this study is shown in Figure 16.
Figure 16: Tube-photometer used in the study.
66
The tube of the photometer used in this research is made of cardboard, and was
procured free of cost from a fabric seller in Beijing, China. PVC pipe is also a relatively
inexpensive material that is appropriate for use as a tube-photometer. The tube used in
this study measures 0.5 m in length, with a 6 cm inside diameter. The end cap fit to one
end of the tube was fashioned from cardboard and packaging tape. Although not
necessary, the end cap can be machined from a more rigid material like wood or plastic.
An Extech 401036 datalogging illuminance meter was used to measure light incident on
the end of the tube. No coating was applied to the internal surface of the photometer
tube. During measurements, dark, opaque fabric was placed over the DuT and the open
end of the tube to ensure that no stray light was measured by the light meter. Due to the
availability, extremely low cost and ease of manufacture, the specified materials are
appropriate for a tube-photometer. Functionally similar materials may be used in place of
the recommended materials, according to local price and availability.
2.1.5 Integrating Sphere – Spectroradiometer System
An integrating sphere with a 1.3-meter diameter was used in this study to measure
the luminous flux of the light sources. The integrating sphere diameter is large enough to
provide sufficient distance between the largest DuT and the sphere wall to permit
adequate multiple reflections of the light within the sphere without undue interference
from the source itself. A high precision spectroradiometer, manufactured by the Beijing
Optical Instrument Factory, was used to measure the light incident on the integrating
67
sphere port. The spectroradiometer has an optical bandwidth of wavelengths from 350 –
780 nanometers, with light intensity measured at 5 nm intervals. The National Lighting
Test Center (NLTC) of China created custom computer software, aptly named Electrical
Light Source Spectral Test and Color Analysis System, which performs sphere
calibrations, compiles the light meter data, applies self-absorption corrections, displays
the measured light intensity over the visible spectrum, and calculates the luminous flux of
the light source. An example of the software output for a single luminous flux
measurement of the Firefly product is shown in Figure 17.
Figure 17: Example of the software output for a measurement of the Firefly luminous flux. Of
importance to this study is the lumen value after being corrected for self-absorption. In this
example, the integrating sphere – spectroradiometer system measured a luminous flux of 24.778 lm.
68
As previously described in Section 1.8.4, the system includes a standard and
auxiliary lamp, as well as baffles for the measurement port and the auxiliary lamp. The
standard lamp was a 15.4 watt, NIST traceable incandescent bulb from OSRAM and the
auxiliary lamp was an OSRAM 10 watt halogen bulb. A thermocouple was fixed inside
of the sphere to monitor the ambient air temperature during testing. The procedure for
measurement of luminous flux specified in CIE 84 was strictly followed for all lumen
measurements conducted in this research.
2.2 Integrating Sphere Calibration
Each integrating sphere has a specific and unique throughput. The throughput of
the sphere is affected by the detector that is placed at a port in the sphere. Because each
sphere and detector combination is unique, the sphere and detector are calibrated as a unit
(Labsphere, 2008a). The integrating sphere – spectroradiometer system used in this
research was calibrated according to CIE 84, which has been previously described in
detail in the Section 1.8.4. Following are the methods used to calibrate the integrating
sphere system to account for non-uniformity of the sphere surface, light distribution and
body color mismatch between the standard and test lamps, and light source self
absorption.
69
2.2.1 Measuring Non-uniform Reflectance of Interior Sphere Surface
The interior surface of integrating spheres, especially older models or those that
have not been recently painted, can exhibit non-uniform reflectance. This can result in
increased measurement error if the standard lamp has a different spatial light distribution
than the DuT. Error due to non-uniform reflectance and mismatched light distribution
can be corrected by a technique that requires characterization of the sphere‟s interior
surface reflectivity and the light distribution of the standard lamp and DuT.
A „map‟ of the sphere‟s interior surface reflectivity is composed of 666 points that
are spaced at 10-degree intervals in the horizontal and vertical planes. A directional light
source is located in the center of the sphere and directed at each of the 666 points. The
illuminance measured by the photometer is recorded at each light orientation.
Accurate rotation of the light source is achieved by a device that is mounted in the
top port of the sphere. The device includes protractors that allow the operator to rotate
the light source at known vertical and horizontal angles. Figure 18 shows the device that
was used to characterize the interior surface reflectivity of the integrating sphere used in
this study. A „reflectance map‟ of the integrating sphere is shown in Table 10 of
Appendix B. Measurement of the sphere‟s interior surface reflectance shows deviations
from the average of up to 7%, which may be large enough to affect the accuracy of
luminous flux measurements made in the sphere.
70
Figure 18: Device for measuring the reflectance characteristics of the integrating sphere‟s interior
surface.
2.2.2 Correcting for Light Distribution Mismatch
The light distribution spatial pattern of the standard lamp is not the same as that of
the lighting products used in this study. A difference between standard lamp and DuT
light distribution patterns can be a source of error when the interior surface of the
integrating sphere exhibits non-uniform reflectivity. The integrating sphere used in this
study was expected to have a slightly irregular surface reflectance that could distort the
luminous flux measurements due to the dissimilar and directional light distributions. As
a result, the measurements made in the integrating sphere must be corrected for light
distribution mismatch.
71
The first step in making this correction is to characterize the light distribution of
the standard lamp and all of the DuTs. A goniophotometer was used to measure the
illuminance on a plane that is parallel to the direction of light emitted by the DuT. Radial
plots of light distribution for all of the lights are shown in Figure 42 through Figure 46 in
Appendix B. All of the lamps have extremely symmetrical light distribution patterns
about the vertical (0o – 180
o ) axis. The assumption, therefore, is that the light
distribution on the single plane can be rotated around the vertical axis to create a three
dimensional shape that characterizes the complete spatial light distribution of the source.
Next, the full width half maximum (FWHM) angle is determined for each light
source. The FWHM angle is a way of expressing how wide of a beam is produced by the
light source. FWHM is the angle in which the light output is at least 50% of the
maximum measured on a plane. For example, the Firefly‟s maximum illuminance
measured by the goniophotometer was 1,296 lux. Half of this value (648 lux) occurs at
about 39o and 318
o, which results in a FWHM angle of 81
o. The FWHM angles for
Solux, Kiran, and the standard lamp are, 81o, and 141
o, and 309
o, respectively. As a
lantern, the Aishwarya‟s light distribution differs from the other, more directional
sources. Aishwarya emits light 360o around the lantern, with a FWHM angle of 99
o.
Computer renderings of the nearly omnidirectional light distribution of the standard lamp,
the simplified cone shaped light distribution from the directional light sources and the
inverse hourglass shape of the Aishwarya lantern are shown in Figure 19.
72
Figure 19: Computer rendering of the simplified three dimensional light distribution shapes for the
standard lamp, top left; directional light sources (Solux, Firefly, and Kiran), top right; Aishwarya
lantern, bottom.
Now that the light distribution for each source and the internal reflectance of the
integrating sphere is determined, the interaction between light and sphere can be
characterized. Here, one must find the average measure of sphere reflectance that occurs
within the FWHM angle of the light source. For ease of calculation, the light sources
(excluding Aishwarya) are placed in the center of the sphere with the light directed
towards the bottom of the sphere (sphere coordinates of 0o horizontal, 0
o vertical). Using
the Firefly as an example, the FWHM angle (approx. 80o) encompasses points on the
sphere‟s interior surface that are between the vertical angles of 0o and 40
o and horizontal
angles from 0o to 360
o. The Aishwarya was also located in the center of the sphere, yet
the FWHM angle spans vertically from 40o to 140
o, and horizontally from 0
o to 360
o.
The reflectance values encompassed by each FWHM angle over this region are averaged.
73
The average reflectance values over the FWHM angle of each product are then
compared to the average reflectance over the FWHM angle of the standard lamp. A ratio
of the standard lamp FWHM reflectance to the DuT FWHM angle reflectance is
calculated according to Equation 6, resulting in a correction factor for the light
distribution mismatch of each DuT. The luminous flux measured by the integrating
sphere-spectroradiometer for each sample is multiplied by the correction factor indicated
in Table 2 in order to correct for the light distribution mismatch.
Table 2: Summary of the light distribution mismatch correction for the DuTs, calculated according
to the full width half maximum (FWHM) angle.
SAMPLE NAME FWHM ANGLE
(DEGREES)
FWHM AVERAGE ILLUMINANCE (lx)
CORRECTION FACTOR
Aishwarya 99 2644.1 0.989
Firefly 84 2528.4 1.035
Kiran 141 2550.1 1.026
Solux 81 2528.4 1.035
Standard Lamp 312 2616.9 -
2.2.3 Correcting for Self Absorption
Since the light sources used in this research are of different size and shape than
the standard lamp, luminous flux measurements made in the integrating sphere require a
self absorption correction specific to each product. Self absorption of the standard lamp
and DuT in the integrating sphere is corrected according to the process described in
Section 1.8.2 and calculated according to Equation 5. A new self absorption correction
was calculated and applied to each round of Simulated Lumen Maintenance testing. The
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custom computer software that accompanies the integrating sphere-spectroradiometer
system at NLTC includes a function that performs the self absorption correction based on
measurements made while illuminating the auxiliary lamp.
2.2.4 Color Mismatch
Luminous flux measurements made using the spectroradiometer are sensitive to
differences in color between the physical body of a test lamp and the standard lamp. It is
possible that the various colors of the DuTs can introduce error in the spectral intensity
measurements that are used to calculate luminous flux. Prior to conducting luminous flux
measurements with the integrating sphere that were used in this study, it was necessary to
understand the extent to which color mismatch affects the measurements for each
product.
An object appears to be of a certain color because its surface reflects visible light
over a range of wavelengths that compose that particular color. All other visible
wavelengths incident on the surface are absorbed by the object. For example, a green
object appears as such since it reflects light with an approximate wavelength of 510 nm,
and absorbs the other visible wavelengths. A body placed in the integrating sphere that is
of a color other than white will absorb some wavelengths and reflect others. When a
spectroradiometer is used to measure light in the sphere, the selective reflection and
absorption of a body within the sphere can result in measurement error.
75
The auxiliary lamp was used to determine the affect of body color on the self
absorption correction for each light source. First, the unilluminated DuT was placed in
the center of the sphere and multiple measurements of the luminous flux from the
auxiliary lamp were made. The DuT was then covered with white paper and the
luminous flux measurements were repeated. Photos of the covered and uncovered Solux
light in the integrating sphere are included in Figure 20. The difference in the average
lumen values between the covered and uncovered product were compared to ascertain
whether excessive error was caused by body color. Results shown in Table 3 indicate
that the DuT body colors resulted in small changes in the luminous flux measured from
the auxiliary lamp. A difference of less than 1% for all of the products is assumed to
have an insignificant effect on the self absorption correction factor that is applied to the
luminous flux measurements. The error associated with color mismatch, therefore, has
been considered negligible in this study.
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Figure 20: Measurements of self absorption color dependency were conducted to verify that the
various body colors of the light sources did not introduce undue error in the determination of
luminous flux. Self absorption of the Devices under Test (DuTs) was measured with the original
colored surface (left) and with a completely white surface (right).
Table 3: Auxiliary lamp luminous flux measurements for all of the light sources indicate that the
error introduced by body color are small enough to be assumed negligible in the study.
SAMPLE NAME AVERAGE LUMINOUS FLUX (lm) DIFFERENCE
UNCOVERED COVERED
Aishwarya 62.05 62.31 0.42%
Firefly 25.84 25.89 0.21%
Kiran 13.90 13.81 0.65%
Solux 71.53 71.78 0.35%
2.3 Simulated Lumen Maintenance Test
Determining the lumen maintenance of a light source according to LM-80 and
Lighting Africa‟s QTM requires that the DuT operate for 6,000 hours (250 days) and
2,000 hours (83 days), respectively. The time required to follow these procedures is
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beyond the scope of this study. More importantly, the intent of this research is to
evaluate the accuracy of the testing devices and methods rather than the lumen
maintenance of the light sources. With these factors in mind, a „Simulated Lumen
Maintenance Test‟ was conducted in order to determine if the tube- and box-photometers
are acceptable substitutes for an integrating sphere for use in actual lumen maintenance
testing.
Like normal lumen maintenance testing, the Simulated Lumen Maintenance Test
uses a power supply to drive the LEDs at a constant current. The simulated test differs
from actual lumen maintenance testing in that the decrease in light output is not caused
by the modes of irreversible degradation previously described in the Section 1.6.2.
Instead, decreases in the DuT light output are achieved by reducing the current through
the LEDs at discrete steps. Each level of current through the LEDs is held constant over
the time required to make light output measurements with each of the three testing
devices.
Ideally, the proportional change in measured light output between each level of
LED drive current should be the same across the integrating sphere, box- and tube-
photometers. Assuming that the luminous flux measured with the integrating sphere is
highly accurate, the illuminance measurements made with the alternative devices can be
compared to the „actual‟ values. By comparing the relative change in light output that is
measured in the low-cost devices to the corresponding measurements made in the
integrating sphere, one can evaluate the accuracy of the alternative low-cost methods. If
78
measurements made in an alternative light measuring device exhibit a highly linear
correlation to those made in the integrating sphere, the alternative device is considered an
acceptable substitute for use in lumen maintenance testing.
2.3.1 Experimental Design
Simply stated, the Simulated Lumen Maintenance Test is a series light output
measurements made at various levels of light intensity. For a single round of testing, one
light source is driven at ten different levels of electrical current, resulting in ten different
light output levels. At each level, the light output is measured once in the sphere, once
with the tube, and twice in the box. The two box-photometer readings are made for two
different DuT orientations within the box. For example, in the first round of Firefly
testing, the product was oriented such that the light was directed towards the back wall of
the box for one measurement and directed towards the lid of the box for the second
measurement. Data for different DuT orientations in the box, especially for highly
directional light sources, are important for investigating the potential for measurement
error caused by rectilinear geometry and irregularities of the interior surface. Three
rounds of Simulated Lumen Maintenance testing are conducted for each of the four
OLPs. A breakdown of the experimental design is shown in Table 4.
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Table 4: The experiment consists of three rounds of testing per product. Each round includes
measurements at ten different light levels made once in the sphere, twice in the box at two different
orientations, and once with the tube.
Each round of testing follows the same procedure that consists of the following steps:
1. Drive the LEDs at a constant current until stability has been reached.
2. Verify that ambient temperature is within acceptable bounds.
3. Specify the test lamp orientations in the box-photometer.
4. Determine the apparatus testing order.
5. Measure the light output using each apparatus.
6. Decrease the LED drive current.
7. Repeat.
Detailed descriptions of each step are given below in Sections 2.3.2 through 2.3.10.
80
2.3.2 Driving the DuT
In order to improve the stability of light output during testing, the batteries and
internal drive circuitry in the DuT were bypassed. The LED array was isolated from the
drive circuitry and an external power supply was connected directly to the LED(s) in each
sample and set to deliver constant current. An adjustment to the LED drive current is
followed by a stabilization period. According to CIE-84, stability is reached when the
variation (maximum – minimum) of at least 3 readings of the light output and electrical
power over a period of 30 min, taken 15 minutes apart, is less than 0.5% (CIE, 1996). A
voltmeter with a precision of 0.001 mV was used to measure the electrical power
delivered to the DuT and light output measurements were conducted with the integrating
sphere system.
2.3.3 Determining the LED Nominal Drive Current
At the start of each round of testing, the LEDs are driven at approximately the
same current that is achieved when the DuT is powered by its battery at nominal voltage.
To determine the current through the LEDs, the battery is removed from the circuit and
replaced by an external power supply. The power supply is set to provide the battery‟s
nominal voltage (refer to Table 1). The DuT is driven at the nominal voltage until a
steady state condition is reached according to CIE-84, as described above. A digital
multimeter and a current shunt circuit, as shown in Figure 15, were used to measure the
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voltage and current through the LED array. This current measurement is the approximate
initial condition for each round of the Simulated Lumen Maintenance Test.
2.3.4 Adjusting the LED Drive Current
A single round of testing for one DuT consists of 40 light output measurements.
The light output is measured at ten different levels using each of the three testing devices.
One measurement is made at each light level with the integrating sphere and tube-
photometer. Two measurements at each light level are made with the box-photometer for
two different orientations of the DuT within the box. The light output at each level is
adjusted by changing the current delivered to the LEDs from the power supply. After
each current adjustment, the DuT is allowed to reach a steady state, which is determined
according to CIE-84. Upon reaching equilibrium, the light output is measured in the box,
tube and sphere. After performing measurements in each of the three testing apparatuses,
the LED drive current is reduced by 5% to 15% and the cycle of stabilization and
measurement is repeated.
Preliminary testing showed that the four products used in this research exhibit
constant light output when the specified stability criteria were met. In fact, for the small
changes in drive current used in this study, the LED light output stabilized more quickly
than the 30 minutes required by CIE-84. Yet, since the stability of light output at each
level is critical for comparison of results across the three testing devices, the stability
criteria established in CIE-84 were strictly followed.
82
2.3.5 DuT Orientation
The placement and orientation of the light sources within the box and sphere and,
in some cases, the position of the tube were documented and photographed to improve
repeatability. For products with broad light distribution patterns, the operator must select
a side or region of the light source that contacts the end of the tube. Products with
directional light sources are shined directly into the tube.
2.3.6 DuT Testing Order
Ideally, the tube, box, and sphere measurements would be made at exactly the
same time to remove the effect of any temporal changes in the DuT light output. Since
the DuT cannot be in all three devices at the same time, the sampling order had to be
randomly assigned. A random number generator was used to determine the order of
testing apparatuses used at each light level. This randomization method effectively
removed bias that may result from the order of testing methods. Even so, a detectable
change in light output over the time to test the DuT in all three devices is assumed
negligible since the stability criteria are met for each light level. To further assure that
the light output did not change during the four measurements, an effort was made to
minimize the time to transfer the DuTs between testing devices.
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2.3.7 Ambient Temperature Regulation
As emphasized in Section 1.6.1, LED light output is highly dependent on
temperature. A constant temperature in and around the testing devices is necessary for
maintaining steady light output from the LEDs. Throughout all of the light output
measurements, the room temperature and temperatures within each testing apparatus
were monitored and held within 2oC of 25
oC, as specified by CIE-84.
2.3.8 Integrating Sphere Procedure
The integrating sphere-spectroradiometer system is the most complex of the three
testing apparatuses. The procedure for operating, calibrating, and measuring luminous
flux of the light sources, therefore, is much more involved than the box- and tube-
photometers. The basic steps for determining the luminous flux of the DuTs are:
1. Calibrate the integrating sphere system using the standard lamp.
2. Determine the self absorption correction using the auxiliary lamp.
3. Measure the test lamp luminous flux.
4. Adjust the measured lumen value according to the self absorption correction and
light distribution mismatch correction factors.
A more detailed, step-by-step description of how the integrating sphere system was
operated in this research is included in Appendix D.
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2.3.9 Box-Photometer Procedure
One of the obvious benefits of the box-photometer is its simplicity of use.
Compared to the integrating sphere, the procedure for measuring light output in the box is
quick and uncomplicated. This is primarily due to the fact that absolute measurements
of luminous flux are not conducted with the box. Since no calibration or correction is
required, the DuT is simply placed in the center of the box and the illuminance measured
by the lux meter is recorded. Below is a detailed description of the procedure followed
for all measurements made with the box-photometer in this study.
1. Connect the test lamp to a power supply and current shunt circuit, using paired,
white insulated wire.
2. Adjust the power supply to the specified current for DuT.
3. Allow the lamp to reach steady state according to CIE-84.
4. Place the DuT on the test stand in the box-photometer. Care is taken to place the
DuT such that its location and orientation can be replicated at each light output level
in a particular round of testing.
5. Route the paired wire through a small notch in the lid-wall interface of the box.
Care is taken to keep the wire at a consistent length and orientation within the box
for all measurements in a particular round of testing.
6. Record the illuminance value measured by the box-photometer‟s lux meter. Adjust
the range of the meter to achieve maximum precision.
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2.3.10 Tube-Photometer Procedure
The tube-photometer is also advantageous for use in lumen maintenance testing
due to its inherent simplicity. The method for measuring lumen maintenance with the
tube is much faster and easier than the integrating sphere, yet slightly more complicated
than the box-photometer method.
As put forth in Section 1.6.3, photometers like the box and tube can be used in
place of an integrating sphere to measure lumen maintenance since they maintain a fixed
geometry between the light source and the photometer sensor. The tube element of the
tube-photometer effectively keeps a constant distance between the DuT and the sensor.
The design of the tube-photometer used in this study, however, does not fix the
orientation of the light source.
To account for this, the “Max. Hold” function that is built into the Extech light
meter is used. When the “Max” button on the light meter is depressed, the meter displays
only the maximum illuminance reading from the sensor. The DuT is placed flush against
the open end of the tube and the light is directed into the tube. Slight adjustments to the
angle between the light source and the tube are made, searching for the maximum
illuminance measured by the light meter. Searching continues until the maximum
illuminance reading displayed on the light meter no longer increases for any orientation
of the DuT. For highly directional light sources like the small task light and flashlight
used in this study, all of the light can be shined into the open end of the tube. More
broadly distributed light sources like the Kiran and Aishwarya products used in this study
require that the operator select a specific region of the light source in which to search for
86
the maximum illuminance. Below is a detailed description of the measurement procedure
followed for all measurements made with the tube-photometer in this study.
1. Connect the test lamp to a power supply and current shunt circuit. Use paired,
insulated wire.
2. Adjust the power supply to the specified current for test lamp.
3. Allow the lamp to reach steady state according to CIE-84.
4. Hold the DuT flush to the open end of the tube with the light directed into the tube.
5. Cover the light source and tube opening with an opaque cloth to inhibit stray light
from entering the tube.
6. Search for the maximum illuminance using the light meter‟s “Max Hold” function.
7. Record the maximum illuminance value measured by the tube-photometer‟s lux
meter. Adjust the range of the meter to achieve maximum precision.
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3 RESULTS
Illuminance data acquired from the box- and tube-photometers for all rounds of
testing all four light sources showed exceptional correlation to the luminous flux data
from the integrating sphere-spectroradiometer system. Graphical and statistical analysis
of the test results is used to evaluate the deviation of the alternative measurements from
the ideal values and to draw conclusions about the use of the box- and tube-photometers
for determining the lumen maintenance of OLPs. Relationships between the low-cost
device measurements and the integrating sphere measurements for each light source are
represented in two different formats: „calibration plots‟ and in terms of relative change in
light output.
3.1 Calibration Plots
Calibration plots show the alternative (box and tube) measurements on the x axis
and the corresponding sphere measurements on the y axis. This comparison is useful for
assessing the proportionality between alternative and sphere measurements. Calibration
plots also provide information for statistical analysis of the test results across the different
light sources. An example of a calibration plot is shown in Figure 21 for a single round
of measurements of the Firefly using the tube-photometer.
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Figure 21: Tube calibration plot for one round of measurements with the Firefly. The linear
equation that best describes the data has a very good fit, with an R2 value of 0.9995.
For the ideal case where no variability exists in the measurement methods, the
illuminance measured by the box- and tube-photometers for a particular DuT can be
multiplied by an experimentally derived factor, with the product equal to the integrating
sphere measurement. The ideal calibration plot is perfectly linear, with a slope that
represents a „calibration factor‟. This simple, linear relationship between ideal measuring
devices is shown in Equation 7. Note that the equation has a y-intercept of zero, which is
due to both ideal methods being „zeroed out‟ when measuring a DuT that is not emitting
light.
y = 0.8572x - 0.0662R² = 0.9995
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
0 5 10 15 20 25 30 35
Inte
grat
ing
Sph
ere
me
asu
rem
en
t (L
um
en
)
Tube-photometer measurement (Lux)
Firefly - Tube Calibration Plot (Round 2)
89
Equation 7: Calibration equation describing the ideal relationship between illuminance
measurements made with the alternative methods and luminous flux measurements made with the
integrating sphere.
where:
= Luminous flux of a light source measured using the integrating sphere-
photoradiometer (lm).
= Illuminance measured by an alternative photometer, such as the tube- or box
photometers used in this study (lx).
C = Calibration factor for a specific light source. When the light source is enclosed by a
cavity like the box-photometer, the calibration factor is applicable to a unique, fixed
orientation of the DuT within the cavity.
The illuminance values measured in the tube- and box- photometers form very
linear calibration plots and the y-intercepts are very near zero. In fact, most of the
calibration plot linear models have y-intercepts that are statistically indistinguishable
from zero. Further discussion of the linear regression confidence intervals is presented in
Section 3.6.2. All of the measurements do contain some degree of error that deviates
from the ideal behavior described in Equation 7. For example, the series of
measurements plotted in Figure 21 have a slightly non-ideal relationship to the
integrating sphere measurements, indicated by an R2 value of 0.995. The y-intercept of
the best fit line is non-zero, but relatively small, at -0.0662. In this particular case, the
origin is encompassed by the 95% confidence interval, indicating that the y-intercept of
the calibration plot follows Equation 7. Calibration plots for all rounds of Simulated
Lumen Maintenance testing are discussed in greater detail in Section 3.3.
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3.2 Relative Change in Initial Light Output
The second format for displaying data from each round of the Simulated Lumen
Maintenance Test is a plot of the relative change in light output. This means of showing
the data is similar to that specified by LM-80 and Lighting Africa‟s QTM. Each
measurement made using the alternative method and the integrating sphere is plotted as a
percentage of the initial light output measurement. The x axis shows the „measurement
number‟, which is the sequence that the measurements of decreasing light output were
conducted. The y axis values are expressed as percentage of the initial light
measurement, calculated by:
Equation 8: Percent of the initial luminous flux for the light output of a product measured in the
integrating sphere.
Equation 9: Percent of the initial illuminance for the light output of a product measured in the box-
and tube-photometers.
where:
= Percent of initial light output for measurement number x (%).
= Initial illuminance for a DuT measured in the integrating sphere (lm).
= Luminous flux of a DuT measured in the integrating sphere for measurement
number x (lm).
= Initial illuminance for a DuT measured by the box- or tube-photometer (lx).
= Illuminance of a DuT measured in the integrating sphere for measurement number x
(lx).
91
Ideally, the percent of initial light output measured at each level in the box- and
tube-photometers would be exactly the same as the integrating sphere. An example of a
plot of relative change in light output for the Firefly using the tube-photometer and
integrating sphere is shown in Figure 22. Notice that in this example, the relative change
in light output measured with the tube very closely follows the sphere.
Figure 22: Relative change in initial light output for the Firefly, as measured by the integrating
sphere and the tube-photometer.
A major consideration for plotting the test data in these relative terms is that all
data points are dependent on the initial light output measurement. This is of concern
because any error in the initial measurement is propagated through all subsequent relative
light output calculations. As a result, the accuracy of the alternative measurements may
appear to be worse than they actually are. The importance of the initial light output
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10
Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Firefly - Round 2
Sphere
Tube
92
measurement in actual lumen maintenance testing and the potential for propagation of
error throughout the entire lifetime test are addressed in greater depth in Sections 3.6.3
and 5.1.
3.3 Box-Photometer Calibration Plots
Previous box-photometer studies indicate that measurement accuracy can be
affected by the orientation and directionality of light sources within the box. Each round
of this experiment, therefore, includes two different orientations of the DuT within the
box. The two highly directional light sources used in testing, the Firefly and Solux, were
placed in the box such that their light was directed towards all four walls and the box lid.
The Kiran and Aishwarya are lantern-like in form and were placed in the box at different
rotational angles in the horizontal plane. The rotational orientations of the Kiran and
Aishwarya for each round of testing are specified by the direction that the integrating PV
module and on/off switch are facing, respectively.
Calibration plots for the box-photometer are shown in Figures 23 through 26,
according to the light source and the specific orientation within the box. Full page
calibration plots are also included in Appendix H. At first glance, one can see that the
data points for the Kiran and Aishwarya are much more tightly grouped than the Firefly
and Solux plots. This is attributed to the directionality of the lights. For DuTs that are
highly directional, changes in testing orientation result in changes to the calibration
factor. Measurements of light sources like the Aishwary and Kiran that have more
93
omnidirectional light distribution are less sensitive to changes in DuT orientation, which
is indicated by calibration factors that are nearly the same for all orientations.
The calibration plots also show that the relationship between the box
measurements and the sphere measurements for all of the DuTs and all of the orientations
are highly linear. Some error is apparent in the box-photometer measurements, indicated
by R2 values that are less than 1 and y-intercepts that are non-zero. None of the testing
rounds have a completely ideal relationship between box and sphere measurements, but
all of the data sets exhibit R2 values that are very near 1 and y-intercepts that are near the
origin. Detailed statistical analysis of the y-intercepts, linearity, and error in the box-
photometer measurements is conducted in Section 3.6.
94
Figure 23: Box-photometer calibration plot for the Firefly
Figure 24: Box-photometer calibration plot for the Kiran
y = 0.653x - 0.3847R² = 0.9994
y = 0.5732x + 0.2106R² = 0.9836
y = 0.6331x - 0.0007R² = 0.9993
y = 0.5322x - 0.0575R² = 0.9994
y = 0.5788x - 2.0243R² = 0.9805
y = 0.5277x - 0.1712R² = 0.9836
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
0 5 10 15 20 25 30 35 40 45 50 55
Sph
ere
me
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rem
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t (L
um
en
)
Box measurement (Lux)
Firefly - Box Calibration Plot
Back Wall
Lid
Right Wall
Baffle
Lid
Front Wall
y = 0.6562x + 0.4786R² = 0.9993
y = 0.6583x + 0.4211R² = 0.9993
y = 0.6518x + 0.0585R² = 0.9994
y = 0.6485x + 0.0693R² = 0.9994
y = 0.6417x + 0.3793R² = 0.9983
y = 0.6428x + 0.416R² = 0.9987
0
2
4
6
8
10
12
14
16
0 2 4 6 8 10 12 14 16 18 20 22 24
Sph
ere
me
asu
rem
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um
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)
Box measurement (Lux)
Kiran - Box Calibration Plot
PV Forward
PV Back
PV Right
PV Left
PV Front
PV Back
95
Figure 25: Box-photometer calibration plot for the Solux
Figure 26: Box-photometer calibration for the Aishwarya
y = 0.5193x - 0.4622R² = 0.9999
y = 0.5752x - 0.5666R² = 0.9999
y = 0.5492x + 2.2295R² = 0.9952
y = 0.4732x + 0.4222R² = 0.9998
y = 0.5161x + 0.2624R² = 0.9999
y = 0.5404x - 1.2725R² = 0.9956
0
10
20
30
40
50
60
70
80
0 20 40 60 80 100 120 140 160
Sph
ere
me
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rem
en
t (L
um
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)
Alternative method measurement (Lux)
Solux - Box Calibration Plot
Lid
Back Wall
Right Wall
Baffle
Lid
Front Wall
y = 0.578x - 0.6286R² = 0.9999
y = 0.5793x - 0.7289R² = 1
y = 0.5714x + 0.0282R² = 0.9998
y = 0.5748x + 0.0503R² = 0.9998
y = 0.5914x - 0.7922R² = 0.9999
y = 0.5901x - 0.7166R² = 0.99980
10
20
30
40
50
60
70
0 10 20 30 40 50 60 70 80 90 100 110 120
Sph
ere
me
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um
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)
Alternative method measurement (Lux)
Aishwarya - Box Calibration Plot
Switch Back
Switch Front
Switch Right
Switch Left
Switch Front
Switch Back
96
3.4 Tube-Photometer Calibration Plots
Calibration plots of the tube-photometer measurements for all four light sources
also show near-ideal behavior. Data from each round of testing have a very linear
relationship between the tube and sphere measurements. Like the box-photometer
calibration plots, y-intercepts of the tube calibration plots are relatively near the origin.
Yet, unlike the box calibration plots, there is not an obvious distinction between the tube-
photometer data for directional and omnidirectional light distributions. Tube-photometer
calibration plots for the Firefly, Kiran, Solux and Aishwarya are shown below in Figures
27 through 30.
97
Figure 27: Tube-photometer calibration plot for the Firefly
Figure 28: Tube-photometer calibration plot for the Kiran
y = 0.8681x - 0.3155R² = 0.9989
y = 0.8572x - 0.0662R² = 0.9995
y = 0.7883x - 0.0709R² = 0.9981
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
0 5 10 15 20 25 30 35
Sph
ere
me
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rem
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t (L
um
en
)
Tube-photometer measurement (Lux)
Firefly - Tube Calibration Plot
Tube-1
Tube-2
Tube-3
y = 2.2426x + 0.4398R² = 0.9981
y = 2.2787x + 0.0199R² = 0.9993
y = 2.2826x + 0.0685R² = 0.9985
0
2
4
6
8
10
12
14
16
0 1 2 3 4 5 6 7
Sph
ere
me
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Tube-photometer measurement (Lux)
Kiran - Tube Calibration PlotTube-1
Tube-2
Tube-3
98
Figure 29: Tube-photometer calibration plot for the Solux
Figure 30: Tube-photometer calibration plot for the Aishwarya
y = 0.6809x + 1.7985R² = 0.9997
y = 0.6779x + 0.907R² = 0.9989
y = 0.7006x + 1.7014R² = 0.9978
0
10
20
30
40
50
60
70
80
0 20 40 60 80 100 120
Sph
ere
me
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rem
en
t (L
um
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Tube-photometer measurement (Lux)
Solux - Tube Calibration Plot
Tube-1
Tube-2
Tube-3
y = 3.85x + 0.2008R² = 0.9957
y = 3.7935x + 0.5366R² = 0.9993
y = 4.0358x - 1.3748R² = 0.9966
0
10
20
30
40
50
60
70
0 5 10 15 20
Sph
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Tube-photometer measurement (Lux)
Aishwarya - Tube Calibration Plot
Tube-1
Tube-2
Tube-3
99
3.5 Relative Change in Initial Light Output
When the light output measurements for the sphere, box and tube in a single
round are plotted as a percentage of the original light output, one can view the data in the
format of an actual lumen maintenance test. More importantly, deviations of the
alternative measurements from the sphere measurements become apparent in these plots.
Data from all three rounds of testing for the Firefly are shown in Figure 31 as a reference
for discussion. Plots of the relative change in initial light output for all products and all
rounds of testing are included in Appendix F. Qualitatively, the graphs in Figure 31
indicate that the box and tube relative measurements correspond closely with the relative
sphere measurements. The plots also show that when the Firefly‟s light is directed
towards the lid of the box-photometer in Rounds 1 and 3, the relative light measurements
noticeably deviate from the sphere measurements. Detailed evaluation of the maximum
percent error for each set of box and sphere measurements is included in Section 3.6.3.
100
Figure 31: Plots of measured relative luminous flux decrease as a percentage of the original light
output for Firefly over three rounds of testing.
40%
50%
60%
70%
80%
90%
100%
1 2 3 4 5 6 7 8 9 10 11 12
Pe
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of
init
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igh
t o
utp
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Measurement Number
Firefly - Round 1
Sphere
Box - Back
Box - Lid
Tube
40%
50%
60%
70%
80%
90%
100%
1 2 3 4 5 6 7 8 9 10
Pe
rce
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of
Init
ial L
igh
t O
utp
ut
Measurement Number
Firefly - Round 2
Sphere
Box - Right Wall
Box - Baffle
Tube
65%
70%
75%
80%
85%
90%
95%
1 2 3 4 5 6 7 8 9 10
Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Firefly - Round 3
Sphere
Box - Lid
Box - Front Wall
Tube
101
3.6 Statistical Analysis of Test Data
Data from the Simulated Lumen Maintenance Tests were evaluated using statistical
methods in order to compare the measurement accuracy of the tube- and box-
photometers. The Simulated Lumen Maintenance calibration plots and relative change in
light output data were used as the basis for analysis. The calibration plots were examined
according to the linear regression R2 value, standard error of the regression, and 95%
confidence interval. The R2 value and standard error of the regression for each round of
testing are tabulated in Appendix I. The tube and box relative light output data were
compared to the integrating sphere measurements on a percent error basis, which is
addressed in Section 3.6.3.
3.6.1 Standard Error of Regression for Calibration Plots
The standard error of the regression is “an overall indication of the accuracy with
which the fitted regression function depicts the dependence of the Y on X” (Zar, 1999).
The standard error of the regression was determined for points on the calibration plot
linear models in order to calculate the 95% confidence intervals. The formula used to
determine the standard error of a point on the regression line is given by Equation 10.
Equation 10: Standard error of a point on the regression line (Zar, 1999).
102
where:
= Standard error of a point on the linear regression model.
= Standard error of the regression.
= Number of samples in each round of measurements.
= Measured illuminance from box- or tube-photometer.
= Mean measured illuminance from a round of testing with the box- or tube
photometer.
and
where:
= Sum of the measured illuminance values for a round of testing with the
box- or tube-photometer.
= Sum of the squared measured illuminance values for a round of testing with the
box- or tube-photometer.
A summary of the standard error for each round of testing is in Appendix I. The
tables include the standard error for each round of testing as a percentage of the average
luminous flux estimated by the linear regression model (SE/ ). These values, ranging
from 0.2% to 3.0%, with an average of 0.9%, indicate that the regression lines accurately
model the calibration plots. Furthermore, comparison of the percentages across all of the
tests highlights specific rounds that deviate from ideal linear behavior more than the
others, which is addressed in Section 4.
103
3.6.2 95% Confidence Intervals of the Calibration Plot
Looking at the 95% confidence interval of the data is also useful for evaluating
how closely the tube-and box-photometers follow ideal measurement accuracy. The
upper and lower bounds for the confidence intervals were calculated according to
Equation 11.
Equation 11: 95% confidence interval for a y-value estimated by the linear regression model
where:
= Sphere luminous flux measurement estimated by the linear regression model for a
particular alternative measurement, Xi.
= t-value of the Student‟s t-distribution as a function of 95% probability and the
degrees of freedom of the data set.
The 95% confidence intervals for all rounds of testing draw tight bounds around
the linear regression models. Examples of two calibration plots that include the 95%
confidence interval bounds are shown in Figures 32 through 34. The linear model is
shown as a solid line and the dashed lines draw the 95% confidence interval bounds. The
tube calibration plot for the Firefly in Figure 32 is representative of the typical results
across all of the methods and products. Qualitatively, the plot shows that the 95%
confidence interval tightly hugs the linear model and that the regression line passes very
near to the origin. Figure 34 shows a box calibration plot for the Firefly shining on the
lid, which is the most non-ideal round of testing. Although the 95% confidence interval
104
is relatively broader in this particular series of measurements, bounding the calibration
plot by +-0.4 lumens (2%) from the predicted values, the measurements are still within a
reasonable tolerance for lumen maintenance testing of OLPs.
Figure 32: Tube calibration plot for the second round of testing with the Firefly, including the best
fit line (solid) and 95% confidence interval bounds (dashed). The inset of the origin illustrates non-
ideality, as the linear model does not pass through the origin.
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
Inte
grat
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Sph
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me
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Tube-photometer measurement (Lux)
Firefly - Tube Calibration Plot (Round 2)
See Enlarged
105
Figure 33: Enlarged section of the tube calibration plot for the Firefly shown in Figure 32.
Figure 34: Box calibration plot for round 3 of testing the Firefly with the light directed at the lid of
the box, including the linear model (bold line) and the 95% confidence interval bounds (thin lines).
This series of measurements showed some of the greatest divergence from ideal behavior, yet still has
an acceptable range of expected error (2%) for use in lumen maintenance testing.
16
17
18
19
20
21
22
23
24
25
26
20 21 22 23 24 25 26 27 28 29 30 31 32
Inte
grat
ing
Sph
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me
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rem
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t (L
um
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)
Tube-photometer measurement (Lux)
Firefly - Tube Calibration (Round 2)with 95% Confidence Interval
15
16
17
18
19
20
21
22
23
24
25
30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
Inte
grat
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Sph
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me
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en
t (L
um
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)
Box-photometer measurment (Lux)
Firefly - Box Calibration Plot (Lid, Round 3)
106
The 95% confidence interval can also be used to evaluate whether the linear
calibration models are expected to pass through the origin. Regression statistics show
that eight of the 36 calibration plot models do not pass through the origin within the 95%
confidence interval range. Although the linear calibration models for these non-ideal
series of measurements do pass near the origin, the expected alternative measurements do
not „zero out.‟ In practice, zeroing out the photometer is not an issue since measurements
at 0 lux are never made in the lumen maintenance testing methods specified by LM-80
and Lighting Africa‟s QTM. More importantly, the fact that the origin is not within the
95% confidence interval of a calibration plot is indicative of some degree of non-ideality
in the measurements. Little emphasis should be placed on these instances of relatively
minor non-ideality, however, since the regression lines project far beyond the range of
measured data. A summary of the calibration plots that are not expected to pass through
the origin is given in Table 5. Notice that the y-intercepts of the regression models are all
relatively near the origin. The difference between the 95% confidence interval bounds
and the origin (ORIGIN – 95% C.I. BOUND) further illustrates that these non-ideal
models narrowly miss the origin.
107
Table 5: Calibration plots whose linear models do not pass through the origin within the 95%
confidence interval. The difference between the 95% confidence interval bound and the origin for
each round of measurements is shown in the right column.
LIGHT SOURCE NAME
LIGHT SOURCE ORIENTATION Y-
INTERCEPT (lm)
ORIGIN - 95% C.I. BOUND
(lm)
Box
Solux Shining on lid - Round 1 -0.46 -0.06
Shining on back wall - Round 1 -0.57 -0.13
Aishwarya On/off switch facing front wall - Round 1 -0.63 -0.48
On/off switch facing back wall - Round 1 -0.73 -0.35
On/off switch facing front wall - Round 3 -0.80 -0.39
On/off switch facing back wall - Round 3 -0.72 -0.23
Tube
Solux Round 1 1.80 1.01
Kiran Round 1 0.44 0.08
3.6.3 Error in Relative Light Output Calculations
The Relative Lumen Decrease plots in Appendix F give additional information
about the applicability of the tube- and box-photometers to lumen maintenance testing.
Calculating the percent decrease in original light output according to Equation 9 results in
propagation of the error from both illuminance measurements. If the initial measurement
is inaccurate, that error is passed on to the subsequent measurements at different light
levels. This propagation of error is visible in Figure 35, where the relative values from
the tube-photometer are all shifted slightly higher than the other methods.
108
Figure 35: Lumen depreciation plot for the third round of testing with the Aishwarya. The relative
measurements made with the tube-photometer are shifted above the other methods due to a low
initial measurement.
Evaluating the data in relative terms adds the error associated with the initial
measurement, which replicates the propagation of error in actual lumen maintenance
testing. Looking at the data from this perspective, therefore, is a more realistic
representation of the error in actual lumen maintenance testing.
The largest discrepancy in a single relative measurement has an error of 7.5%.
This outlier occurs in Round 1 of testing the Firefly in the box-photometer, with the light
directed towards the box lid. The average percent error across all of the relative light
measurements in the box and tube are much lower, at 1.4% and 1.5%, respectively. In
terms of the accuracy required for lumen maintenance measurement in the QTM and
50%
55%
60%
65%
70%
75%
80%
85%
90%
95%
100%
1 2 3 4 5 6 7 8 9 10
Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Aishwarya - Round 3
Sphere
Box - Switch Front
Box - Switch Back
Tube
109
ISM, this degree of error is acceptable. A summary of the maximum percent error for all
sets of relative light output measurements is included in Appendix G.
3.6.4 Analysis of Variance (ANOVA) for R2 of Calibration Plots
An Analysis of Variance (ANOVA) General Linear Model (GLM) method of
statistical analysis is used to determine if there is a statistically significant difference
between the accuracy of measurements made in the box- and tube-photometers. In
addition, the GLM compares the accuracy of box and tube measurements according to the
specific light source that is being measured. A summary of the three null hypotheses and
the GLM test results is shown in Table 6.
Table 6: Summary of null hypotheses tested in ANOVA and interpretation of the statistical test
results.
Null Hypothesis (HO) ANOVA Result
(Reject / Fail to Reject)
Interpretation of Result
R2 of the calibration plot
linear model does not
depend on the light source.
Fail to Reject
No statistically significant
difference in measurement
accuracy is attributed to the
different light sources.
R2 of the calibration plot
linear model does not
depend on the method used
to measure the light output.
Fail to Reject
No statistically significant
difference in measurement
accuracy between the tube-
and box-photometers.
Response of R2 to the light
measurement method does
not depend on the light
source.
Reject
Statistically significant
differences exist in the
measurement accuracy for
specific light source/testing
apparatus combinations.
110
One way of comparing the accuracy of measurements between the different
products, testing devices and rounds of testing is the coefficient of determination. “The
coefficient of determination, R2, is the proportion of variability in a data set that is
accounted for by the statistical model” (Steel & Torrie, 1960). In this analysis, R2
indicates the goodness of fit of a linear model for the relationship between illuminance
measurements made with low-cost methods and the corresponding luminous flux
measurements made with the integrating sphere. The R2 value serves as a measure of the
ideality of the box and tube measurements, where the perfect round of measurements can
be described by a linear equation with R2 = 1. By using R
2 values from the calibration
plots as the continuous response variable in a GLM, one can generate statistical data that
rejects or fails to reject specific hypotheses about the accuracy of the testing methods.
The null hypotheses for analysis of data from this study are:
HO, 1: R2 of the calibration plot linear model does not depend on the light source.
HO, 2: R2 of the calibration plot linear model does not depend on the method used to
measure the light output.
HO, 3: Response of R2 to the light measurement method does not depend on the light
source.
The R-squared values of the calibration plot linear models are useful for
comparing the accuracy of each series of measurements. Yet, one complication
associated with the R2 values used in this particular study is that each round of testing
includes two series of box measurements, each with its own linear regression model. For
use in this statistical analysis, the two R2 values for each round of box-photometer
111
measurements are averaged. This yields 24 data points that are the GLM response
variables (four DuTs, each with three rounds of measurements, using two measurement
apparatuses).
Another complication encountered when generating the response variables for the
statistical analysis is that the R2 values of the calibration plots are very similar in
magnitude. The R2 values range from 0.982 to 0.999, with an average value of 0.998.
The histogram in Figure 36 shows how the data are right-skewed, with a majority of R2
values lying between 0.997 and 1. The data grouped near R2=1 are so similar that many
are equal up to two and even three significant digits (i.e. 0.99 and 0.999). In order to
differentiate between such similar magnitudes, the R2 values had to be calculated out to
as many digits as possible. This was accomplished by using the Microsoft Excel “Data
Analysis - Regression” tool, which reports the R2 values out to 15 digits.
112
1.00000.99750.99500.99250.99000.98750.98500.9825
12
10
8
6
4
2
0
R-Squared
Fre
qu
en
cy
Histogram of R-Squared
Figure 36: Histogram of R-squared values for the experimental calibration plots shows that the data
are right-skewed and two outliers are less than 0.99.
Minitab statistical analysis software was used to create a GLM with the high
precision R-squared values as the response variable. The statistical model consists of
three different categorical predictor variables: Name, Round, and Method. Name
identifies which OLP was used (i.e. Firefly, Kiran, Solux, or Aishwarya). Round
identifies the series of parallel measurements conducted with the box- and tube-
photometers (three rounds of measurements were conducted for each Name). Method
identifies whether the tube- or box-photometer was used to make the light output
measurements. The structure of the experiment for use in the GLM is shown
schematically in Table 7 and a summary of the categorical predictor variables is given in
Table 8.
113
Table 7: Hierarchy of experimental design for ANOVA.
Table 8: Summary of the categorical predictor variables used in the Simulated Lumen Maintenance
statistical analysis.
General Linear Model: R2 versus Name, Round, Method
Factor Type Levels Values
Name Fixed 4 Firefly, Kiran, Solux, Aishwarya
Round Random 12 1, 2, 3 for each Name
Method Fixed 2 Box, Tube
When creating the GLM, the relationship between the factors in the experimental
design must be specified. First, Round is nested within Name. This means that each OLP
is subjected to three unique rounds of testing that cannot be repeated exactly with the
other light sources. Secondly, Method is crossed with Name. This means that all of the
DuTs are measured with the same box- and tube-photometers in all rounds of the
experiment.
The types of factors used in the GLM must also be specified according to the
experimental design. Both Name and Method are fixed factors, indicating that they are
controlled in the experiment. Round is specified as a random factor in the GLM. This is
due to the fact that the exact electrical current and sequence at which LEDs are being
driven can never be exactly replicated.
114
The experiment is described by the following equation for the GLM:
Equation 12: General Linear Model used for statistical analysis of the Simulated Lumen
Maintenance test data.
Y = NAME + ROUND(NAME) + METHOD + METHOD*NAME + ERROR
where:
ROUND(NAME) = Testing round is nested in the light source
METHOD + METHOD*NAME = Testing device is crossed with the light source
ERROR = Error not accounted for by the model
Using Minitab software, the 24 R-squared values were input into the GLM
described in Equation 12. The normal probability plot of R2 and the „Versus Fits‟ plot,
shown in Figure 37, indicate that the data are right-skewed. Most of the R-squared
values lie between 0.997 and 1.0, with only a few less than 0.997. The residuals are not
normally distributed, which shows that the R2 values do not have equal variance. This
violates the normality assumption for a general linear model. Also, note that some fitted
values in the „Versus Fits‟ plot are greater than 1. This model is incorrect since R2 is, by
definition, never greater than one.
115
3210-1-2-3
99
95
90
80
70
60
50
40
30
20
10
5
1
Standardized Residual
Pe
rce
nt
Normal Probability Plot(response is R SQUARE)
1.0051.0000.9950.9900.985
3
2
1
0
-1
-2
-3
Fitted Value
Sta
nd
ard
ize
d R
esid
ua
l
Versus Fits(response is R SQUARE)
Figure 37: Residual plots of the R-squared values for the experimental calibration plots. The
Normal Probability Plot and Versus Fits plot indicate that the data are right-skewed and not
normally distributed.
A transformation of the response variable, therefore, is necessary. Equal variance
of the R2 values is achieved by applying the following transformation:
Equation 13: Transformation applied to the R2 data in order to normalize a skewed distribution.
The natural logarithm (ln) of the quantity (1 – R2) adjusts the data such that they
exhibit normal distribution and equal variance. The natural log is negative in order to
keep the transformed values positive. As shown in Figure 38, the transformed data have
normally distributed residuals and equal variances, thereby meeting the assumptions for a
general linear model.
116
9.68.88.07.26.45.64.84.0
7
6
5
4
3
2
1
0
-ln(1-R^2)
Fre
qu
en
cy
Histogram of -ln(1-R^2)
3210-1-2-3
99
95
90
80706050403020
10
5
1
Standardized Residual
Pe
rce
nt
Normal Probability Plot(response is -ln(1-R2))
10987654
2
1
0
-1
-2
Fitted Value
Sta
nd
ard
ize
d R
esid
ua
l
Versus Fits(response is -ln(1-R^2))
Figure 38: The Histogram of R2 data after applying the transformation shows normal distribution.
The Normal Probability Plot has equal variance and the Versus Fits plot also shows a distribution
that satisfies the assumptions of the general linear model.
117
A GLM of the same form as Equation 12 was generated using Minitab for the
transformed R2 values. A summary of the statistical results is shown in Table 9.
Table 9: Statistical results from the general linear model for the transformed R2 values (R
2TRANS) of
the calibration plots.
ANOVA for R2TRANS
Source DF Seq. SS Adj. SS Adj. MS F P
NAME 3 7.9800 7.9800 2.6600 1.32 0.335
ROUND(NAME) 8 16.1607 16.1607 2.0201 2.92 0.076
METHOD 1 1.4723 1.4723 1.4723 2.13 0.183
NAME*METHOD 3 15.6348 15.6348 5.2116 7.53 0.010
Error 8 5.5395 5.5395 0.6924
Total 23 46.7874
S = 0.832129 R-Sq = 88.16% R -Sq (adj) = 65.96%
The general linear model has a moderately high adjusted R2 value of 65.96%,
indicating that the GLM accounts for nearly 66% of the variability of the data. An
adjusted R2 value of this magnitude is a fair approximation of the data points and is
acceptable for use in evaluating the null hypotheses.
A p-value of 0.335 for the Name term indicates that the difference in R2 values of
the calibration curves for all four DuTs have a 33.5% chance of being ascribed to chance
alone. In other words, it is statistically plausible that the measurement accuracy for each
of the four light sources used in testing are the same. Furthermore, an F statistic of 1.32
means that the variance in the transformed R2 due to brand is 1.32 times greater than that
118
due to error. The first null hypothesis that „R2 of the calibration plot linear model does
not depend on the light source,‟ therefore, cannot be rejected.
A p-value of 0.183 and F-statistic of 2.13 for the Method term indicates that the
second null hypothesis, too, cannot be rejected. The difference in R2 values of the linear
models for the calibration plots cannot be attributed the method alone.
The third null hypothesis, that the „response of R2 to the light measurement
method does not depend on the light source,‟ is rejected. The Name*Method term has a
p-value of 0.010 and an F-statistic of 7.53, which indicates that the interaction between
Name and Method causes statistically significant differences in R2 values. The tube- and
box-photometers have statistically different measurement accuracy for some light sources
used in the experiment. The interaction plot in Figure 39 demonstrates how the mean R2
value of the calibration plots for the Firefly measured in the box-photometer is
significantly less than all other Name*Method combinations. This outlier supports the
results of the ANOVA, indicating that rejection of HO, 3 is justified. The error in the
Firefly‟s box-photometer measurements are discussed in greater detail below.
119
TubeBox
1.000
0.998
0.996
0.994
0.992
0.990
METHOD
Me
an
Aishwarya
Firefly
Kiran
Solux
NAME
Interaction Plot for R-SquareFitted Means
Figure 39: Interaction plot showing how the mean R2 value varies across the box- and tube-
photometer testing methods and four light sources. Calibration plots of the Firefly measured in the
box-photometer exhibit significantly smaller R2 values than the other light source-measuring device
combinations.
120
4 DISCUSSION OF RESULTS
The Simulated Lumen Maintenance Test data indicate that the tube- and box-
photometers can be used to accurately measure the relative decrease in light output of
various OLPs. Qualitatively, the near-ideal behavior of the box and tube is easily
identifiable in the highly linear calibration plots and tightly grouped relative light output
plots. Quantitative analysis of the box and tube measurements not only indicates a close
correlation to the sphere measurements, but also allows for further comparative
conclusions to be drawn.
The Simulated Lumen Maintenance Tests were evaluated from several different
statistical perspectives in order to compare measurement accuracy and identify strengths
and weaknesses of the tube- and box-photometers. The R2 values of the calibration plots,
ranging from 0.982 to 0.999, are a clear indication of the highly linear, near-ideal
relationship between the tube, box and integrating sphere measurements. The 95%
confidence intervals for the calibration plots indicate that light measurements made with
the box- and tube-photometer have little deviation from the linear model. The relative
light output plots for tube and box measurements also exhibit a very close correlation to
the integrating sphere measurements in most cases. The average percent error across all
of the relative light measurements in the box and tube are 1.4% and 1.5%, respectively.
Simple comparisons of these error metrics across all rounds of testing are useful for
identifying apparatus-DuT combinations that had relatively high levels of error.
121
Analysis of variance of the calibration plot R2 values shows that the tube and box are
equally accurate in measuring the light output of the light sources used in this study. The
ANOVA also confirms that the outlying rounds of Firefly measurements did, in fact,
have statistically significant deviation from the error in other rounds of testing.
4.1 Worst Case: Error Analysis of Firefly in the Box-Photometer
A closer look at the rounds of testing that have the greatest amount of variability
is useful for understanding some possible ways in which the low-cost test methods are
prone to measurement inaccuracy. Evaluating how the measurements deviate from ideal
behavior allows for conclusions to be drawn about potential improvements to the testing
devices and informs recommendations for their use in quality assurance testing of OLPs.
When measured in the box-photometer, the Firefly exhibited the greatest
deviation from ideal behavior. Error in the measurements was primarily due to two
rounds of testing with the light directed towards the box-photometer lid. The calibration
plots for these two outliers have R2 values of 0.984 and 0.981, indicating that the linear
models for these two „worst case‟ rounds of testing account for about 98% of the
variability in the data sets. The standard error of the regression as a percentage of the
average predicted values (SE/ ), listed in Appendix I also indicate that these two
rounds of Firefly measurements have relatively elevated levels of error (3.0% and 1.8%).
Although statistical analysis does show that more error is present when the Firefly light
122
output is measured in the box, one must keep in mind that the degree of variability in
even this worst case scenario is quite small.
In the case of the Firefly oriented towards the box lid, the slight non-linearity of
the data is most likely due to two main factors. One source of measurement error may be
the particular orientation of the light source. When the Firefly‟s directional light (FWHM
angle of 81o) shines towards the lid of the box, the light may strike the photometer sensor
after a single reflection. As described earlier, hollow cavity photometers like the box-
photometer require that the light reflect off the interior surface at least twice before
striking the sensor. Directing the Firefly towards the box‟s lid may allow some of the
light to strike the photometer sensor after the first bounce, resulting in a detectable
increase in measurement error. The measurement error may also be attributed to the
Firefly‟s flexible neck. A relatively high degree of adjustability introduces more
variability in the orientation of the light source. Repeating the exact same orientation of
the light source for each measurement in the box-photometer is much more difficult for
the Firefly. This results in increased measurement error, especially since the Firefly is a
directional light source. Statistically significant increase in the measurement error of the
Firefly in the box-photometer highlights the importance of maintaining a constant
location and orientation of a DuT in the box. Care should be taken to set up an easily
repeatable placement of the DuT. Gooseneck-style lamps like the Firefly and other
highly adjustable products should be fixed in a configuration that restricts movement of
the light source.
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4.2 Sources of Error
Deviations of light output measured with the box-photometer from the integrating
sphere measurements can be primarily attributed to random error that is due to
unpredictable changes in the test. The most likely source of random error in box-
photometer measurements is inconsistency in the way that the operator conducts the tests.
Inaccuracy in the box-photometer measurements occur when the operator fails to repeat
the same placement and orientation of the DuT throughout the lumen maintenance test.
Even seemingly small changes in the orientation of the DuT within the box can yield
inaccurate test results. Fortunately, random errors can be reduced by making repeated
measurements.
The dominant cause of error in tube-photometer measurements is also likely due
to operator error. The method for measuring light output with the tube-photometer
requires the test operator to search for and identify the maximum illuminance. Failure to
find the maximum illuminance will result in a measured value that is too low. Like the
box-photometer, error due to misidentification of the maximum illuminance with the
tube-photometer can be reduced by making multiple measurements. The maximum
illuminance value from the repeated tube-photometer measurements can be assumed to
be the most accurate light output value.
Systematic errors, on the other hand, cannot be reduced by repeating
measurements. Systematic errors in the box and tube measurements, while extremely
small, are most likely due to the apparatuses, themselves. Some possible sources of
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systematic error may include irregularities in the tube and box cavities, light intrusion in
the cavities, and the illuminance meters. The low-cost illuminance meters used in the
box- and tube-photometers may have introduced a relatively small degree of error. The
precision of the low-cost meters is 0.01 lux for a range of measured values up to 20 lux,
and 0.1 lux for measured values up to 200 lux. A majority of the box- and tube-
photometer measurements made in this study lie in the 20 – 200 lux range, which is
typical for OLPs currently on the market. While higher quality, more precise illuminance
meters may be used in place of the Extech meters used in this study, it is unlikely that any
significant measurement accuracy will be achieved. Furthermore, the Extech meter is
relatively inexpensive, which is an important criterion for selecting components used in
the low-cost testing apparatuses.
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5 CONCLUSIONS AND RECOMMENDATIONS
The results of this study clearly indicate that the box- and tube-photometer can be
used to accurately measure the relative decrease in light output of OLPs. The box- and
tube-photometers, therefore, are recommended for use in the QTM and ISM Long-Term
Lumen Degradation Test. While the statistical analyses do point out some divergences
from perfect correlation to the integrating sphere measurements, the box- and tube-
photometers have proven to be highly accurate substitutes for an integrating sphere in
lumen maintenance testing. Nonetheless, the type and magnitude of measurement errors
identified in this research point to potential flaws in the low-cost testing devices.
5.1 Impact of Error on Lumen Maintenance Test Results
The current versions of Lighting Africa‟s QTM and ISM indicate that the box-
and tube-photometers are acceptable substitutes for an integrating sphere for use in the
Long-Term Lumen Degradation Test. Approval of the alternative light measuring
devices is based on the assumption that additional error associated with box and tube
measurements is negligible. Results from this study indicate that while the box- and
tube-photometers can accurately measure the relative change in light output, there are
instances where the alternative measurements deviate from the sphere by up to 7.5%. If a
high-error measurement occurs at the beginning or end of the lumen maintenance test,
significant miscalculation of the product‟s life may result. Consider for example, a
126
product that reaches its L70 lifetime just before 2,000 hours and, as a result, does not
meet the Lighting Africa minimum performance target. If the final relative light output
measurement has an error on the order of 7.5%, the maximum seen in this study, there is
a possibility that the product may have actually met the performance target. As
mentioned above, the best way to address this type of error is to make repeated
measurements. Each light output measurement, especially the initial reading, should
therefore be repeated at least twice in order to identify incorrect readings.
5.2 Benefits and Disadvantages of the Box-Photometer
The box-photometer has been used for quality assurance testing of OLPs at
SERC, FISE and the University of Nairobi in Kenya. Experience has shown that boxes
can be affordably and easily constructed according to the specifications shown in
Appendix J. The box-photometer also has a good track record of use for illuminance and
luminous flux measurements. The device has been verified as a legitimate light
measuring apparatus by authoritative sources and, more recently, it has been used
successfully at the aforementioned institutions.
A major strength of the box-photometer is its relative ease of use. Light
measurements made in the box can be conducted very quickly and simply. The box-
photometer is also versatile. The box is currently a critical piece of equipment in light
testing labs for conducting the QTM Autonomous Run Time and Solar Run Time tests, in
addition to the Long-Term Lumen Degradation test.
127
The box-photometer does, however, exhibit some weaknesses. This study has
shown that the box is susceptible to small errors when measuring the light output of
highly directional and adjustable light sources. These errors, which can generally be
avoided by repeated measurements and diligent repetition of DuT orientation within the
box, may actually be less important than the cost and size of the device. Box-
photometers constructed for the University of Nairobi lighting lab cost approximately
100 USD each, not including the cost of the light meters. This is a relatively minor
expense when compared to the cost of other equipment required for a fully functional
lighting test center. Yet, from the perspective of a low-budget laboratory in a developing
country, or a lighting manufacturer seeking to conduct low-cost in-house testing, this may
be a considerable expense.
The physical size of the box-photometer has already proven to be an issue at the
University of Nairobi. The small room that houses their lighting lab had to be
strategically organized to fit all of the necessary equipment. As testing operations
expand, space is at a premium, and any additional equipment must be compact in size.
An additional box-photometer requires nearly 1m2 of floor space. Other lighting test
centers with similar budgetary and space constraints are also likely to experience similar
problems.
128
5.3 Benefits and Disadvantages of the Tube-Photometer
The tube-photometer excels in its physical simplicity and exceptionally low cost.
The device consists of only three parts: a tube, an end cap and an illuminance meter.
Both the tube and end cap can be constructed of common, inexpensive (often free)
materials. No specialized tools are needed for assembly of the tube-photometer. The
device used in this study was constructed using a utility knife and packaging tape. In
addition, the tube-photometer does not present the size issues encountered by the box-
photometer. The device used in this study was 0.5 m long, with a 6 cm diameter. Unlike
the box-photometer, the tube does not require any floor space in the lighting laboratory.
The tube is lightweight and easily portable. The tube-photometer can be stored in any
convenient location, as long as the light meter sensor remains fixed to the tube in the
same orientation and free of dust.
While the tube-photometer clearly offers financial, constructability, and spatial
advantages over the box-photometer, the apparatus does have its own particular
weaknesses. Firstly, the tube-photometer, as configured in this study, cannot be used for
the QTM Autonomous Run Time and Solar Run Time tests. The tube is intended solely
for the measure of relative change in light output for lumen maintenance testing.
Secondly, measurements made with the tube-photometer are not as simple or as quick as
the box-photometer. For each reading, the operator must „search‟ for the maximum
illuminance using the light meter‟s “Max. Hold” function. This not only requires more
time and skill using the device, but introduces the possibility for increased operator error.
129
When measuring DuT light output, the light source must be held flush to the open
edge of the tube as angular adjustments are made to the orientation of the light. For
lantern-shaped lights like the Aishwarya, the operator has to „search‟ for a maximum
illuminance over the surface of the product. The operator must continue searching for the
maximum lux value until the light meter‟s “Max. Hold” function no longer increases.
This presents the problem of „giving up the search‟ before the actual maximum
illuminance has been recorded by the meter. The tube-photometer may be especially
prone to this type of measurement error when more than one operator is conducting the
lumen maintenance test for a particular DuT.
5.4 Multiple Test Operators
An important caveat of this study is that all of the measurements made in the
Simulated Lumen Maintenance Tests were conducted by the same experienced operator.
The tests were performed by the author who understands the theories and concepts
behind the measurements and is very familiar with all of the equipment and methods. In
addition, the author had a substantial stake in carefully executing the measurements.
Many technicians employed to conduct these tests by developing country lighting
laboratories or off-grid lighting manufacturers may not have the same level of
comprehension, familiarity, or meticulous execution of the test methods. The
measurement accuracy for the tube- and box-photometers described herein, therefore,
may be greater than the accuracy achieved by similar tests conducted by less experienced
130
operators. While user experience and skill level may affect measurement error, one must
keep in mind that accurate use of the box- and tube-photometers is much simpler and
easier than integrating sphere and goniophotometer systems.
Additionally, lumen maintenance testing in lighting laboratories is likely to be
conducted by more than one operator. This too, may lead to decreased measurement
accuracy due to inconsistencies between test operators. In the case of the box-
photometer, different people may place the DuT in the box in slightly different
orientations. The tube-photometer may be even more susceptible to operator-based
variability if one operator does not thoroughly „search‟ for the maximum illuminance
value. With these additional sources of variability, one must take caution when
translating the results and recommendations from this study to actual implementation in
lighting laboratories. When training lighting lab technicians and selecting the most
appropriate means of measuring lumen maintenance, one must take into account the
operators‟ skills, levels of expertise, and attention to detail. Since the variability
introduced by multiple, less skilled technicians was not addressed in this study, further
research that explores the significance of error introduced by these factors may be
warranted.
5.5 Potential Improvements to Lumen Maintenance Testing Devices
The results of this study point to variability in the light source orientation as a
major contributor to the error in tube- and box-photometer measurements. In the context
131
of quality assurance testing of OLPs in developing countries, these errors are quite
acceptable when considering the economic and ease-of-use benefits achieved by the low-
cost testing devices. The next logical step in developing the ideal lumen maintenance
testing device is to explore how to minimize measurement error while maintaining or
even improving the benefits exhibited by the box- and tube- photometers.
The Lighting Research Center (LRC) at Rensselaer Polytechnic Institute is
currently contracted with Lighting Africa to conduct quality assurance testing of select
OLPs available in the African market. LRC has taken a slightly different approach to
lumen maintenance testing that may have drastically reduced the measurement error
while maintaining the ease-of-use and low-cost characteristics of the box- and tube-
photometers. They have constructed a simple apparatus, shown in Figure 40, that
maintains the DuT in a fixed position over the course of the lumen maintenance test by
affixing the product to a block of wood.
Figure 40: Light measurement apparatus used at the Lighting Research Center for lumen
maintenance and run time testing of off-grid lighting products. Photo courtesy of Erik Page.
132
The most novel aspect of LRC‟s light measurement device, however, is the use of
low-cost photodiodes to measure the light output of the DuTs. Each DuT is fixed in a
cavity and shines light on a dedicated photodiode. The photodiodes, manufactured by
OSRAM, cost about 1 USD each and have an accurate V() spectral response. The
photodiodes are connected to a computer that uses LabView software to convert the
voltage signals to an illuminance reading and automatically samples and records the
illuminance measurements at specified time intervals. This method for measuring the
relative change in light output eliminates the human error associated with the box- and
tube-photometers, but it does require more space and knowledge of a complex software
package.
As demand for low-cost performance testing of OLPs continues to grow, new
iterations of test methods and improvements to testing devices, like the apparatus created
by LRC, are likely to emerge. Nonetheless, this study confirms that the tube- and box-
photometers are both effective tools for measuring the lumen maintenance of OLPs. Yet,
when selecting the most appropriate device for lumen maintenance testing, lighting
laboratories must use discretion to choose apparatuses according to their particular time,
training, monetary, spatial, and accuracy constraints.
133
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137
APPENDIX A: LIGHT SOURCES USED IN TESTING
138
Figure 41: Off-grid lighting products used in this study. Clockwise from top left: Aishwarya Wow,
D light Nova, Solux LED-50, Barefoot Firefly.3
3 Product images downloaded from the following websites:
Aishwarya: www.akashdeep.org; Kiran: www.metaefficient.com; Firefly: www.enejipwop.com;
Solux: www.solux.org
139
APPENDIX B: INTEGRATING SPHERE INTERNAL REFLECTANCE MAP
140
Table 10: Illuminance map describing irregularity in the interior integrating sphere surface used in testing. The horizontal and vertical
angles are measured in reference to the bottom of the integrating sphere. The illuminance values are measured by the photospectrometer
when the light source was directed to the indicated horizontal and vertical angles.
141
APPENDIX C: DEVICE UNDER TEST (DuT) LIGHT DISTRIBUTION PLOTS
142
Figure 42: Radial light distribution of Firefly product, measured in lux on a vertical plane.
Figure 43: Radial light distribution of Aishwarya product, measured in lux on a horizontal plane.
06 12 1824
3036
4248
5460
667278849096102
108114
120126
132138
144150
156162168174180
186192198204210
216222
228234
240246
252258264270276282288294
300306
312318
324330
336342348354
06 121824
3036
4248
5460
667278849096102
108114
120126
132138
144150
156162168174180
186192198204210
216222
228234
240246
252258264270276282288294
300306
312318
324330
336342348354
143
Figure 44: Radial light distribution of Solux product, measured in lux on a horizontal plane.
Figure 45: Radial light distribution of Kiran product, measured in lux on a vertical plane.
06 12 18 24
3036
4248
5460
667278849096102
108114
120126
132138
144150
156162168174180
186192198204210
216222
228234
240246
252258264270276282288294
300306
312318
324330
336342348354
06 12 18 24
3036
4248
5460
667278
84
90
96
102108
114120
126132
138144
150156162168174
180186192198204
210216
222228
234240
246252
258
264
270
276
282288
294300
306312
318324
330336342348354
144
Figure 46: Radial light distribution of the standard lamp, measured in lux on a vertical plane.
06 12 18 24
3036
4248
5460
667278849096102
108114
120126
132138
144150
156162168174180
186192198204210
216222
228234
240246
252258264270276282288294
300306
312318
324330
336342348354
145
APPENDIX D: INTEGRATING SPHERE PROCEDURE
146
Each day that the integrating sphere was used to measure luminous flux, it was calibrated
according to the known light output of the NIST traceable standard lamp. The following
steps were followed to perform the sphere calibration.
1. Turn on the spectroradiometer and the standard lamp power supply.
2. Insert the standard lamp in the socket connected to the power supply.
a. Use cotton gloves so no oils are left on the optics.
3. Use the bulb‟s element as a reference for location in the center of the sphere and for
maintaining the same rotational orientation (for improved repeatability).
4. Slowly increase the standard lamp power supply to 220V AC (to reduce thermal
shock).
5. Allow at least 20 min. for the lamp to reach steady state temperature and light
output.
6. Close the spectroradiometer aperture.
7. “Zero” the spectroradiometer using the accompanying computer software.
8. Open the aperture to the largest setting.
9. Using the software, calibrate the sphere system according to the standard lamp‟s
rated lumen output.
10. Save the standard lamp measurement file to the computer for subsequent
calculations of test lamp luminous flux.
11. Slowly decrease the standard lamp power supply to 0 V to minimize thermal shock.
Each round of testing requires that the test lamp luminous flux measurement be corrected
for self absorption. The following steps were followed at the beginning of each round of
testing to determine the self absorption correction factor that was applied to each
luminous flux measurement.
1. Connect the auxiliary lamp to a power supply and current shunt circuit.
2. Slowly increase the power supply voltage until 0.84715 A is reached to reduce
thermal shock.
3. Allow at least 20 min. for the auxiliary lamp to reach steady state.
4. Using the computer software, measure the luminous flux of the auxiliary lamp with
the unilluminated standard lamp in the sphere.
147
5. Save the measurement file on the computer for use in the self absorption correction.
6. Remove the standard lamp from the sphere.
7. Mount the unilluminated test lamp in the center of the sphere.
a. Hang using thin white cord.
b. Orient so that the light source is even with the middle of the baffle.
c. For lamps with focused light distribution, the beam is directed to the
bottom of the sphere.
8. Using the software, measure the luminous flux of the auxiliary lamp.
9. Save the measurement file on the computer for use in the self absorption correction.
10. Slowly decrease the auxiliary lamp‟s power supply voltage to zero to reduce thermal
shock.
Luminous flux of the test lamps at each light output level was measured and corrected for
self absorption and light distribution mismatch according to the following steps.
8. Connect the test lamp to a power supply and current shunt circuit
a. Use paired, white insulated wire
9. Adjust the power supply to the specified current for test lamp.
10. Allow the lamp to reach steady state according to CIE-84.
11. Using the software, measure the luminous flux of the test lamp.
12. Save the measurement file to the computer.
13. Using the software, select the appropriate files for self-absorption correction and the
luminous flux calculation.
a. Test lamp auxiliary lamp measurement file
b. Standard lamp auxiliary lamp measurement file
c. Test lamp measurement file
14. Save the light intensity vs. wavelength plot
15. Apply the light distribution mismatch correction to determine the luminous flux of
the test lamp.
148
APPENDIX E: RAW TEST DATA
149
Table 11: Raw data from comparison testing of the Firefly product in the integrating sphere, box-
photometer and tube-photometer.
150
Table 12: Raw data from comparison testing of the Kiran product in the integrating sphere, box-
photometer and tube-photometer.
151
Table 13: Raw data from comparison testing of the Solux product in the integrating sphere, box-
photometer and tube-photometer.
152
Table 14: Raw data from comparison testing of the Aishwarya product in the integrating sphere,
box-photometer and tube-photometer.
153
APPENDIX F: RELATIVE LUMEN DECREASE PLOTS
154
Figure 47: Plots of measured relative luminous flux decrease for Firefly for three rounds of testing.
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10 11 12Pe
rce
nt
of
init
ial l
igh
t o
utp
ut
Measurement Number
Firefly - Round 1
Sphere
Box - Back
Box - Lid
Tube
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10
Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Firefly - Round 2
Sphere
Box - Right Wall
Box - Baffle
Tube
65%
70%
75%
80%
85%
90%
95%
100%
0 1 2 3 4 5 6 7 8 9 10Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Firefly - Round 3
Sphere
Box - Lid
Box - Front Wall
Tube
155
Figure 48: Plots of measured relative luminous flux decrease for Kiran for three rounds of testing.
30%
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Kiran - Round 1
Sphere
Box - PV Front
Box - PV Back
Tube
30%
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10
Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Kiran - Round 2
Sphere
Box - PV Right
Box - PV Left
Tube
60%
65%
70%
75%
80%
85%
90%
95%
100%
0 1 2 3 4 5 6 7 8 9 10Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Kiran - Round 3
Sphere
PV - Front
PV - Back
Tube
156
Figure 49: Plots of measured relative luminous flux decrease for Solux for three rounds of testing.
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Solux- Round 1
Sphere
Box - Lid
Box - Back
Tube
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10
Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Solux- Round 2
Sphere
Box - Right
Box - Baffle
Tube
30%
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10
Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Solux- Round 3
Sphere
Box - Lid
Box - Front
Tube
157
Figure 50: Plots of measured relative luminous flux decrease for Aishwarya for three rounds of
testing.
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10
Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Aishwarya - Round 1
Sphere
Box - Switch Back
Box - Switch Front
Tube
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10
Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Aishwarya - Round 2
Sphere
Box - Switch Right
Box - Switch Left
Tube
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10Pe
rce
nt
of
Init
ial L
igh
t O
utp
ut
Measurement Number
Aishwarya - Round 3
Sphere
Box - Switch Front
Box - Switch Back
Tube
158
APPENDIX G: MAXIMUM ERROR IN RELATIVE LUMEN DECREASE
159
Table 15: Maximum error in the calculation of relative decrease in the initial light output according to light source, round of testing, testing
apparatus, and orientation within the box-photometer (where applicable).
160
APPENDIX H: CALIBRATION PLOTS
161
Figure 51: Comparison of integrating sphere lumen measurement to alternative method (tube- and box-photometer) lux measurements for
each round of Firefly Simulated Lumen Maintenance testing.
y = 0.653x - 0.3847R² = 0.9994
y = 0.5732x + 0.2106R² = 0.9836
y = 0.8681x - 0.3155R² = 0.9989
y = 0.6331x - 0.0007R² = 0.9993
y = 0.5322x - 0.0575R² = 0.9994
y = 0.8572x - 0.0662R² = 0.9995
y = 0.5788x - 2.0243R² = 0.9805
y = 0.5277x - 0.1712R² = 0.9836
y = 0.7883x - 0.0709R² = 0.9981
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
0 5 10 15 20 25 30 35 40 45 50 55
Sph
ere
me
asu
rem
en
t (L
um
en
)
Alternative method measurement (Lux)
Firefly Calibration Plots Box-1
Box-2
Tube-1
Box-3
Box-4
Tube-2
Box-5
Box-6
Tube-3
162
Figure 52: Comparison of integrating sphere lumen measurement to alternative method (tube- and box-photometer) lux measurements for
each round of Kiran Simulated Lumen Maintenance testing.
y = 0.6562x + 0.4786R² = 0.9993
y = 0.6583x + 0.4211R² = 0.9993
y = 2.2426x + 0.4398R² = 0.9981
y = 0.6518x + 0.0585R² = 0.9994
y = 0.6485x + 0.0693R² = 0.9994
y = 2.2787x + 0.0199R² = 0.9993
y = 0.6417x + 0.3793R² = 0.9983
y = 0.6428x + 0.416R² = 0.9987
y = 2.2826x + 0.0685R² = 0.9985
0
2
4
6
8
10
12
14
16
0 2 4 6 8 10 12 14 16 18 20 22 24
Sph
ere
me
asu
rem
en
t (L
um
en
)
Alternative method measurement (Lux)
Kiran Calibration Plots Box-1
Box-2
Tube-1
Box-3
Box-4
Tube-2
Box-5
Box-6
Tube-3
163
Figure 53: Comparison of integrating sphere lumen measurement to alternative method (tube- and box-photometer) lux measurements for
each round of Solux Simulated Lumen Maintenance testing.
y = 0.5193x - 0.4622R² = 0.9999
y = 0.5752x - 0.5666R² = 0.9999
y = 0.6809x + 1.7985R² = 0.9997
y = 0.5492x + 2.2295R² = 0.9952
y = 0.4732x + 0.4222R² = 0.9998
y = 0.6779x + 0.907R² = 0.9989
y = 0.5161x + 0.2624R² = 0.9999
y = 0.5404x - 1.2725R² = 0.9956
y = 0.7006x + 1.7014R² = 0.99780
10
20
30
40
50
60
70
80
0 20 40 60 80 100 120 140 160
Sph
ere
me
asu
rem
en
t (L
um
en
)
Alternative method measurement (Lux)
Solux Calibration Plots Box-1
Box-2
Tube-1
Box-3
Box-4
Tube-2
Box-5
Box-6
Tube-3
164
Figure 54: Comparison of integrating sphere lumen measurement to alternative method (tube- and box-photometer) lux measurements for
each round of Aishwarya Simulated Lumen Maintenance testing.
y = 0.578x - 0.6286R² = 0.9999
y = 0.5793x - 0.7289R² = 1
y = 3.85x + 0.2008R² = 0.9957
y = 0.5714x + 0.0282R² = 0.9998
y = 0.5748x + 0.0503R² = 0.9998
y = 3.7935x + 0.5366R² = 0.9993
y = 0.5914x - 0.7922R² = 0.9999
y = 0.5901x - 0.7166R² = 0.9998
y = 4.0358x - 1.3748R² = 0.99660
10
20
30
40
50
60
70
0 10 20 30 40 50 60 70 80 90 100 110 120
Sph
ere
me
asu
rem
en
t (L
um
en
)
Alternative method measurement (Lux)
Aishwarya Calibration Plots Box-1
Box-2
Tube-1
Box-3
Box-4
Tube-2
Box-5
Box-6
Tube-3
165
APPENDIX I: R2 VALUES AND STANDARD ERROR OF TEST RESULTS
166
Table 16: R-squared values and standard error of the linear regression for each round of Simulated Lumen
Maintenance testing, including a calculation of the standard error as a percentage of the average luminous
flux estimated by the linear regression model (SE/ ).
167
168
APPENDIX J: BOX-PHOTOMETER CONSTRUCTION PLANS AND
INSTRUCTIONS
169
170
171
172
173
174
ASSEMBLY INSTRUCTIONS FOR BOX-PHOTOMETER
1. Cut the “MAIN PIECES FOR ASSEMBLY” to the dimensions shown on
PHOTOMETER BOX PLANS – Use a table saw if available
2. Pre-drill pilot holes on 65cm x 60cm wall pieces
3. Apply glue along 2,5cm x 60cm area of wall pieces with pilot holes
4. Use four clamps (one at top, one at bottom for each side)to hold the four walls
together as shown on in the top view of PHOTOMETER BOX PLANS
5. Drive finish nails into pre-drilled pilot holes
6. Allow 12 hours for glue to cure
7. Remove clamps
8. Check butt joints for structural integrity
9. Apply glue to bottom edges of walls
10. Align and clamp bottom piece to walls
11. Allow 12 hours for glue to cure
12. Remove clamps
13. Check for structural integrity
14. Cut 4cm x 4cm feet (as shown in front view of PHOTOMETER BOX PLANS)
and glue to four exterior corners of bottom piece. The weight of the photometer
box will hold the feet in place while the glue cures
15. Apply glue to 2,5cm width of “TOP RIM” pieces along top outside perimeter of
walls
16. Place “TOP RIM” pieces on outside walls as shown in PHOTOMETER BOX
PLANS and clamp in place
17. Allow 12 hours for glue to cure
18. Remove clamps
19. Check for structural integrity
20. Drill hole in corner of photometer box for placement of PVC section – Use a hole
saw if available
175
21. Cut PVC pipe to appropriate length and miter cut to tightly fit against hole in
photometer box
22. Affix PVC section to photometer box with caulk sealant, making sure to seal
against all possible light intrusion at joint
23. Assemble test stand and attach with wood screws to center bottom of photometer
box as shown in top view
24. Cut plastic screens and drill holes for insertion of dowels
25. Drill holes at appropriate angles and locations for screen dowels, refer to top view
(interior)
26. Insert screen dowels into holes in photometer box walls. No glue should be
required
27. Place top lid piece onto photometer box
28. Align hinge as shown in top view (lid)
29. Pre-drill pilot holes and attach hinge with wood screws
30. Pre-drill hole for handle (as shown in top view) and attach to lid
31. Paint ALL interior surfaces of photometer box. Several coats are recommended
32. Refer to the Lighting Africa Quality Test Method, Section 3.2 for additional
details (Lighting Africa, 2010c). Available for download at:
http://lightingafrica.org/resources/technical-research.html
176
APPENDIX K: TUBE-PHOTOMETER CONSTRUCTION PLANS
177
ASSEMBLY INSTRUCTIONS FOR TUBE-PHOTOMETER
1. Cut the tube to a length of 0.5 m
2. Cut a piece of cardboard into a square with sides that are at least twice as long as
the tube diameter
3. Create the end cap by cutting a circle out of the center of the cardboard square
that is of the same diameter as the photometer sensor.
a. It is important that the sensor fit snugly into the hole so that no light
intrusion occurs and the sensor remains in a fixed position.
b. If more advanced tools and materials are available, a more robust and rigid
end cap can be constructed of wood or other equivalent materials.
4. Fit the end cap to one end of the tube.
a. The cardboard square is placed such that the hole is located at the center of
the tube opening. The cap is formed by bending the cardboard over the
end of the tube.
5. Using packaging tape, duct tape, or an equivalent method, affix the end cap to the
end of the tube.
a. The end cap must be solidly mated to the tube such that it does not shift
and no light can pass between the cap and the tube.
6. Insert the photometer sensor into the end cap and affix with packaging tape, duct
tape, or the equivalent.
a. The sensor must be solidly mated to the end cap such that it does not shift
and no light can pass between the sensor and the cap.
b. Check that no unwanted light is intruding into the tube by blocking the
open end of the tube and reading the photometer measurement. The
photometer must read 0 lx.
178
APPENDIX L: LIST OF EQUIPMENT USED IN THE STUDY
179
Test Apparatus
Equipment Name
Manufacturer / Model Specifications
Box-photometer
Thermocouple Reader
Omega HH806AU 0.1oC precision
Thermocouple Omega K-type, insulated
Lux Meter Extech 401036
Datalogging, precision: 0.01 - 0.1lx (depending on range)
Box Custom fabricated* Refer to Appendix J
Tube-photometer
Thermocouple Reader
Omega HH806AU 0.1oC precision
Thermocouple Omega K-type, insulated
Lux Meter Extech 401036
Datalogging, precision: 0.01 - 0.1lx (depending on range)
Tube w/ end cap Custom fabricated** 0.5m long, 6cm diameter
Integrating Sphere
Thermocouple Reader
Omega HH806AU 0.1oC precision
Thermocouple Omega K-type, insulated
Spectrophoto-meter
Beijing Optical Instrument Factory, WDM1-1
Optical bandwidth: 350 - 780 nm; resolution: 5nm
Software for integrating sphere luminous flux calculation
NLTC, proprietary: Electrical Light Source Spectral Test and Color Analysis System
Calculates luminous flux of DuT based on spectrophotometer reading, standard lamp and auxiliary lamp lux measurements
DC Power Supply DH1719-1 1 mA precision
Standard Lamp OSRAM
15.4W incandescent, NIST traceable
Auxiliary Lamp OSRAM 10W halogen
Sphere 1.3m diameter -
LED Driver
Power Supply DH1719-1 1 mA precision
Digital Multimeter
Fluke 179 Precision: 0.01 mA, 0.1 mV
Digital Multimeter
Solartron Schlumberger 7150
0.001 mV precision
Resistor 0.01 High precision
Goniophotometer NLTC, custom -
*Refer to APPENDIX J for a detailed description of the Box-photometer assembly.
**Refer to APPENDIX K for a detailed description of the Tube-photometer assembly.