Sensitivity Analysis of a 500 W Proton Exchange Membrane Fuel Cell Stack by Design of Experiments

8/3/2019 Sensitivity Analysis of a 500 W Proton Exchange Membrane Fuel Cell Stack by Design of Experiments

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Sensitivity Analysis of a 500 W Proton Exchange Membrane Fuel

Cell Stack by Design of experiments

Document by: Bharadwaj

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In this paper, the influences on fuel cell performance of gas pressure and flow rate parameters are studied. The fuel

cell is operated at various pressure and gas flow rates are regulated by mass flow controllers placed upstream of thestack. In this study, four types of control factors considered are pressures of the fuel and oxidant and the flow rates

of the fuel and oxidant to select the optimized conditions for fuel cell operation. Each factor has two levels, leadinga full factorial design requiring 24 experiments leading to 16 experiments and fractional factorial experiments, 24-1,

leading to 8 experiments. The experimental data collected were analyzed by statistical sensitivity analysis by

checking the effect of one variable parameter on the other. The mixed interaction between the factors was also

considered along with main interaction to explain the model developed using the design of experiments. From the

analysis maximum fuel cell performance was found to be hydrogen flow rate, oxygen flow rate and the interaction

between the hydrogen pressure and oxygen flow rate compared to all other factors and their interactions. Thesefractional factorial experiments, presently applied to fuel cell systems, can be extended to other ranges and factors

with various levels, with a goal to minimize the variation caused by various factors that influence the fuel cell performance but with less number of trials compared to full factorial experiments.

Keywords: PEMFC, statistical analysis, ANOVA, factorial design, stack.

1. Introduction:

Polymer electrolyte membrane fuel cell (PEMFC) is

the most promising system among several differentkinds of fuel cells due to their various advantages

such as easy start-up, room temperature operation, no

liquid electrolyte, and high current density. To

achieve high current density, the optimal operating

conditions need to be identified for fuel cell systems

in addition to design parameters such as membrane,

catalyst particle size, quantity, and nature of gas

diffusion layers. There are many variables in theoperation of fuel cell systems, viz., fuel cell

temperature, reactant pressure, reactant flow, relativehumidity, and load. These parameters are related

among themselves to nonlinear relations, leading to

an impact on the fuel cell voltage [1, 4]. This is

concerned with minimizing the effect of uncertainty

or variation in design parameters on a design without

eliminating the source of the uncertainty or variation.

The robust design is less sensitive to variation in

uncontrollable design parameters than the traditionaloptimal designs. Robust design has found many

successful applications in engineering and is presently expanded to fuel cell systems with a goal to

minimize the variation caused by uncontrollable

noise factors such as ambient temperature, operating

environment, and natural phenomena that are difficult

to control [5-8]. The robust design can also help to

minimize the caused by control factors such as

pressure, flow rate and humidity. Improvement of

power and stabilization of cell performance under different operating conditions are important for

developing a practical PEMFC system. In general

these desirable parameters combinations were

decided by one factor experiments and the analysis is

done by fixing the other parameters, where theinfluence of other parameters is not considered. In

addition, a large number of experiments are needed to

analyze the performances of a given fuel cell systemare to identify the parameters of a physical model. In

order to evaluate the impacts of the physical control parameters on the fuel cell operation, the design of

experiment (DOE) method, developed by Fisher [9,

10], is being used, in particular, to reduce the number

of tests when many parameters were considered.

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Recently, this method is being used by many

researchers in fuel cell technology for the

development of fuel cells, materials for fuel cells, and

optimal solution for operating conditions, which

determine the most significant parameters [11-14].Grujicic et al. [15] studied the cathode and optimized

the distributor geometry by analysis of variance(ANOVA) method. The effect of material and

manufacturing variations on membrane electrode

assembly pressure distribution has been analyzed by

Vlahanos et al. [16]. The experimental analysis of

combined heat and power performance of a PEMFC

stack of 800 w capacity has been studied by factorialdesign method and showed that cathode

stoichiometry has a positive effect on electrical

power and negative effect on thermal power [17]. In

another detailed study by Guvelioglu and Stenger

[18], the main and interaction effects of PEMFC

design parameters have been studied with five factors

such as channel width, GDL thickness, GDL

conductivity, and GDL porosity. They found that thestrongest interaction occur between the channel size

and the GDL conductivity, while the weakestinteraction effects are observed between the GDL

thickness and the porosity.

2. Experimental

2.1 Experimental setup:

The Proton Exchange Membrane Fuel Cell

(PEMFC) stack was developed at the GASHUB,

Singapore by making use of 20 membrane electrode

assemblies [MEAs] made by a proprietary processand graphite plates with triple serpentine channel

geometry. The MEAs were made using a treated

Toray paper as a gas diffusion electrode and 20%

Pt/C as electro catalysts for both anode and cathode

and NafionTM membrane 111 from DuPont denomour

as an electrolyte. The area of each electrode was

found to be 100 cm2. The coolant circuit was also

introduced in the system manifold for the removal of heat. The heat developed by the stack is removed by

the water cooled system. The details of the stack are

given in table 1.

2.2 Test station:

The PEMFC test bench, used for the cell

management, was developed by K-Pas InstronicEngineers, Chennai which has partially designed in

our laboratory.

Table 1 Technical specifications of fuel cell

Number of cells 20

Cell area(cm2) 100

Operating temperature(0C) 30

Operating pressure max. 3 bar

Media inlet:

Cathode humidified oxygen

Anode humidified hydrogen

cooling Demineralised water

The apparatus consists of gas flow control systems,

temperature control, pressure control and humidifier

systems, electronic-load bank, milliohm meter for the

resistance measurement and a icomputerized dataacquisition system. All the settings of the test bench

concerning gas flow, temperature, humidity and gas

pressure were controlled through the data acquisitionsystem connected to the computer. Fig. 1 presents a

schematic diagram of the experimental apparatus.

Hydrogen in the anode side and oxygen or air in the

cathode side was provided from a pack of pressurised

gas tanks. The fuel gas flow rates were regulatedwith electronic thermal mass flow controllers. Both

the anode and cathode fuel gases were humidified by

forcing the gas through a gas–liquid equilibrium

stage. In order to maintain uniform cell and

humidifiers temperatures, three heaters driven with a

National Instruments Field Point controller were

used. The temperatures of the cell, the anode and of

the cathode humidifiers were measured through threethermocouples. Furthermore, two thermocouples

were also located near the gas inlet lines. Theelectric load bank was a semiconductor device that

allows high currents to be drawn at low voltages.

The load was air-cooled and rated at 2000W. A

digital AC milliohm meter was placed in parallel both

to the electric load and the fuel cell. This device

provided a quick and accurate measurement of the

total impedance magnitude of the cell and the load at

a specific frequency. The ohmic resistance of the cellcan be extracted after correction of the impedance of

the load. During the fuel cell operation, the wet

gases were fed to the fuel cell and then diffused to the

MEA through the gas diffusion layers (GDLs) whilecirculating in the gas channel. The un-reacted gases

and the water produced during the electrochemical

reactions were released from the fuel cell. The

exhausted gases pass through the backpressureregulators and then exit through the vent. A personal

computer running Windows XP2000 and a Scada-

based software with a variety control, data logging



and displaying features were employed for the

experimental monitoring and controlling.

Table 2 Measurement ranges and accuracy of

measurement devices of test facility

Measurementdevices(Make:K-Pas

Instronic Engineers)

Measurement range and

accuracy

Power station

electronic load

Input:230v, AC50Hz Voltage:

0-100ADC

Capacity:2000Watts Features:

3 ½ Digital meter for volts-

19.99volts 4

½ Digital meter for Amps-

19.999 Amps

Flow measuring

device (Mass flowcontroller)

Control range: 2–100% of full

scaleAccuracy: 1 % of full scale

PID controller Temperature controller withsensors

Range:0-1000C

Operating voltage: 230v AC

Type of thermocouple : J Type

Figure 1 Diagram of Experimental Apparatus for the

PEMFC Testing

Figure 2 Experimental setup of fuel cell test station

Range of parameters studied in the experiments:

In this study considered the effect of four variables,

pressures of the fuel (H2), pressure of oxygen (O2),

flow rate of the fuel and flow rate of the oxidant.

These variables are studied an objective to select the

optimized conditions for fuel cell operation. For each

variable experiment were conducted at lower and

Factors

Levels

Low High

A : hydrogen pressure (bar) 1.7 2.15

B: oxygen pressure (bar) 2.15 2.78

C: hydrogen flow rate(lpm) 0.88 1.81

D: oxygen flow rate (lpm) 0.95 1.91



higher levels (two levels). A full factorial design

required 2n experiments, where 2 is the level of the

variable and n is the number of variables considered,

leads to 16 experiments and the fractional factorial

experiments, 24-1, leading to 8 experiments. Therange of parameters is listed in Table 3.

Table 3 The range of parameters studied in theexperiment

2.2. Experimental procedure:

The 500 W Proton Exchange membraneFuel cell stack was connected to the power station

and the gas connections were given to the stack. Test

station was turned on and gas lines were opened.

Before starting the process Fuel cell was purged with

Nitrogen gas to remove any impurities in the stack.

Initially from the literature and by conducting the

preliminary tests the variable levels were found as,

the fuel (H2) pressure range 1.70–2.15 bar, oxidant(O2) in the pressure range 2.15 – 2.78 bar, the fuel

(H2) flow rate is ranging from 0.88 to 1.81 lpm and

flow rate of oxidant (O2) ranging from 0.95 to 1.91

lpm. These four factors were considered at two

levels i.e... Low level and high level, like wise 16

experiments were conducted and temperature of stack

was maintained at 300c. After continuous operation

of stack by supplying fuel and oxidant at givenlevels, open circuit voltage (OCV) was reached to 18

volts without load for about 1 hr. When we draw the

load as a current mode by step by step for given

current set point for the given ranges of flow rates

and pressures of fuel and oxidant. It was observedthat, when current increases the voltage decrease

proportionally and increase the power. To maintain

the temperature at 300C heat was removed by water

circulation system showed in figure 2. When it

reached the minimum voltage 10 volts, it was trip off and the load was off. Like wise 16 experiments were

carried out to maximize the performance of fuel cell

stack. Experimental data was analyzed by using

design of experiment technique - full factorial design

and fractional factorial design methods.

2.3 Design of Experiments.

The design of Experiments (DOE) method

has been adapted to achieve the objectives by setting

the limits for the pressure and flow rate for the

reactants. The influence of these parameters on the

fuel cell is critical. For the method of factorial design

the experiments were conducted for four variables at

two different levels. The four factors are fuel

pressure, fuel flow rate, oxidant pressure, and oxidantflow rate. The DOE experiments were conducted for

the fuel (H2) pressure range 1.70–2.15 bar, oxidant

(O2) pressure range 2.15 – 2.78 bar, the fuel (H2) flow

rate range from 0.88 to 1.81 lpm and flow rate of

oxidant (O2) range from 0.95 to 1.91 lpm. The

observations were made at all the combinations of 24

experiments that can be formed for different levels of

the factors, called treatment combinations. Thefactors that were set at the low level, indicated as

(−1) and those at the high level as (+1). The

particular combination of treatments was made using

the Yates notation. In the fractional factorial method,

the number of observations was reduced to 24−1

(eight) treatment combinations. The response of theobservations was power (watts) with factors such as

reactant pressure and flow rate at two different levels.

3. RESULTS AND DISCUSSIONS

The fuel cell stack of 500 W capacities was

presented with humidified reactants (hydrogen and

Oxygen) at the open circuit potential for about 1 hr.

The stack was operating when the stack was reached

the open circuit voltage as 18 volts. Load was turnedon with increase of current step by step for 30mts and

subsequently voltage was decreased with increasing

the power. The polarization data were collected for

the stack at the stack temperature of 300C. The

current voltage characteristics of 500W stack are

shown in figure 1 at a hydrogen operating pressure of

2.15 bar with 1.9Lpm. From the figure one can see

that the stack can deliver a power of around 205 Wwith oxygen. The full factorial and fractional

factorial design of experiments are conducted for a

500 W PEMFC stack.

Current density (mA/cm2)

0 20 40 60 80 100 120 140 160

V o l t a g e ( V o l t s )

13

14

15

16

17

18

19

P o w e r ( w a t t s )

0

50

100

150

200

250

Volatge VS Current density

Power VS Current density

Figure 3 current, voltage - power characteristics of

the fuel stack at 300c, H2 flow = 1.81 lpm,

O2 flow= 1.91 lpm

3.1 Full Factorial design:



For the Design of experiments (DOE), the

response considered here is the fuel cell power output

as a function of pressure and flow rates of reactants

(Hydrogen and Oxygen). Four types of control

factors namely, the pressure of the Hydrogen, the pressure of the oxygen, the flow rate of the Hydrogen

and the flow rate of the oxygen are considered toselect the optimized conditions for fuel cell operation

as given in table 3.

The levels and factors were chosen by taking into

account the limits of the fuel cell stack and also the

test bench. However, the linearities for these factors

and levels are considered in the specified range. Thefull factorial design for the four factors with various

treatment combinations is shown in table 4.

The Analysis Of Variance (ANOVA) is a commonly

used tool to study and estimate the factor that

influence the process. Initially, ANOVA is performed

for the main effects, pressure of the Hydrogen (A),

pressure of the oxygen (B), flow rate of the Hydrogen

(C) and the flow rate of the oxygen (D). Thenanalysed for interaction effects of two factors like

AB, AC, AD, BC, BD, CD, interaction effects of three factors, ABC, BCD, CDA, DAB and interaction

effects of four factors, ABCD and analysis results are

summed in table 5.

Table 4. Full Factorial design format for four factors

The main eight effects of the four factorsare shown in figure 4 for comparison

called graph of the average effects.

H2 pressure (A)

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

M e a n o f P o w e r ( W )

100

120

140

160

180

200

220

O2

Pressure (B)

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

M e a n O f t h e P o w e r ( W )

100

120

140

160

180

200

220

H2

Flow (C)

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5


100

120

140

160

180

200

220

O2 Flow (D)

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5


100

120

140

160

180

200

220

Figure 4 Influence of Four Factors on Power(Y)

Table 5 Analysis of variance for power including

main and interaction effects for 24experiments

The four graphs represent the maximum power

obtained from the 16 experiments as well as the

average of these 16Y values and the average of the

stack power, when the x factor is at two levels,

namely, low and high. From these graphs we can

observe that the factor with a greater slope is the

most significant factor for getting maximum power .

S.NO.Hydrogen

Pressure (A)

Oxyge Pressure

(B)

Hydrogen

Flow rate (C)

oxygen Flow

rate (D)

1 1.7 2.15 0.88 0.95

2 2.15 2.15 0.88 0.95

3 1.7 2.78 0.88 0.95

4 2.15 2.78 0.88 0.95

5 1.7 2.15 1.81 0.95

6 2.15 2.15 1.81 0.95

7 1.7 2.78 1.81 0.95

8 2.15 2.78 1.81 0.95

9 1.7 2.15 0.88 1.91

10 2.15 2.15 0.88 1.91

11 1.7 2.78 0.88 1.91

12 2.15 2.78 0.88 1.91

13 1.7 2.15 1.81 1.91

14 2.15 2.15 1.81 1.91

15 1.7 2.78 1.81 1.91

16 2.15 2.78 1.81 1.91

Source Effect

Sum of

squares

%

contribution

Degrees

of

Freedom

Mean

Square F p

A

-

11.375517.5625 2.155707 1 517.56252.853746 0.152

B -2.625 27.5625 0.114801 1 27.5625 0.151975 0.712

C 64.12516448.06 68.50807 1 16448.0690.69164 0

D 14.875 885.0625 3.686387 1 885.0625 4.880074 0.078

AB -0.375 0.5625 0.002343 1 0.5625 0.003102 0.958

AC

-

13.625742.5625 3.092858 1 742.56254.094355 0.098

AD 14.625855.5625 3.563516 1 855.56254.7174170.0819

BC -2.875 33.0625 0.137709 1 33.0625 0.182301 0.687

BD 0.375 0.5625 0.002343 1 0.5625 0.003102 0.958

CD 13.625742.5625 3.092858 1 742.56254.094355 0.098

Error 906.8125 5 181.3625



It can be seen from the graphs that the slope of factor

C, which is Hydrogen flow, is higher compared to all

other factors and hence it is very significant on the

cell performance. The most insignificant factor in

this set of experiments is the oxygen pressure (B), asthe graph is almost parallel to X axis. The

contribution from each factor can be obtained fromthe ANOVA table as shown in table 5 representing

the source of variability, degrees of freedom

associated with each factor, sum of squares, and

mean squares due to each factor.

Fisher statistics shows the ratio of meansquares with the factor and the p value for the Fisher

statistics. The p value determines whether the factor

is statistically significant or not. Generally, the mean

values are significant if the p value is less than 0.05.

From the table 5 we can see that the C factor

contribution is more around 68% and the next

contributor is Oxygen flow rate (D) factor, which is

around 4%. From the p value one can also find thatthe C factor is statistically significant, as it is less

than 0.05. The model equation can be written asequation (3.1) shows the fitted parameters for the

analysis of mean interactions. Hence the first order

interactions effects were also considered and are

tabulated in table 5.

The average two factor interactive effects are shown

in figure 5. It is observed that the interactive effects

of Hydrogen pressure - Hydrogen flow (AC),

Hydrogen pressure - oxygen flow (AD) and hydrogenflow - oxygen flow (CD) are significant compared to

the other two factor interactive effects, AB, BC and

BD.AB interaction

A

-1 .5 -1.0 -0.5 0.0 0.5 1.0 1.5

p o w e r ( W )

100

120

140

160

180

200

220

B -

B +

A C in t e rac t ion

A

-1.5 -1.0 -0.5 0.0 0.5 1 .0 1.5

p o w e r , ( W )

100

120

140

160

180

200

220

C -

C+

AD In teract ion

A

-1 .5 -1 .0 -0 .5 0.0 0.5 1 .0 1 .5

P o w e r ( W )

100

120

140

160

180

200

220

D -

D +

BC in te ract ion

B

-1.5 -1 .0 -0 .5 0 .0 0 .5 1.0 1 .5

p o w e r ( W )

10 0

12 0

14 0

16 0

18 0

20 0

22 0

C -

C +

BD Interaction

B

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

p o w e r ( W )

100

120

140

160

180

200

220

D -

D +

C D In te ra ct ion

C

-1 .5 -1 .0 -0 .5 0 .0 0 .5 1 .0 1 .5

p o w e r ( W )

100

120

140

160

180

200

220

D -

D +

Figure 5 Interaction effects of four factors at two

levels on the fuel cell stack Performance.

Figure 6 (a) and 6 (b) shows the normal

probability plots of the data collected i.e. effect and

for residual respectively, considering both the mainand interaction effects. It can be inferred from the

above figures that the data follow the normaldistribution and the interaction effects in the residual

plots are random.

Effect

-20 0 20 40 60 80

N o r m a l % p r o b a b i l i t y

0.001

0.01

0.050.10.20.5

12

5

10

2030

50

70

80

90

95

9899

99.899.9

99.95

99.99

99.999

AC

ABC

B ABC

ABCD

AB

ABDBD

BCD

CD

ADD

ACD

C

(a)

Residual

-40 -30 -20 -10 0 10 20 30

N o r m a l % p r o b a b i l i t y

1

2

5

10

20

30

50

70

80

90

95

98

99

(b)

Figure 6(a) Normal probability plot of the effects of the 24

Factorial, 6 (b) Normal probability plot of Residuals

From table 6 it can be observed that theaverage three factor interactive effect of Hydrogen

pressure - Hydrogen flow - oxygen flow (ACD) is

contribute 3.686 % and the remaining three factor

interactive effects, ABC, ABD and BCD contribute

less than 0.1%. Hence ACD effect will be significant



compared to the remaining factors. The four factor

interactive effect of Hydrogen pressure – oxygen

pressure - Hydrogen flow - oxygen flow (ABCD) is

contributed 0.006508 %. Hence its effect is

insignificant.

Hence it can be concluded that the effect of C and D are significant compared to A and B.

The ANOVA is also carried out by using

MINITAB statistical software. The data developed

from this MINITAB statistical software was

presented in the figures 7, 8 and 9.

The data collected for the fuel cell power

response followed the normal distribution

as shown in figure 7 (a) and the graphical

summary shown in figure 7 (b). The box

plot shows the pattern of variation in the

experimental data and also shows thatthere are no outliers or extreme values or

unusual observation.

Table 6 Analysis of variance data for the factors A, C

and D

25020015010050

99

95

90

80

70

60

50

40

30

20

10

5

1

power (watts)

P e r c e n t

Mean 152. 4

StDev 37.56

N 16

AD 1.834

P-Value <0.005

Normal

Probability Plot of power

210200190180170160150140130120

power (watts)

Boxplot of power

Figure 7 (a) Probability plot of the fuel cell power (b) Box plot of the experimental data.

40200-20-40

99

90

50

10

1

Residual

P e r c e n t

200175150125100

20

0

-20

-40

Fitted Value

R e s i d u a l

20100-10-20-30

6.0

4.5

3.0

1.5

0.0

Residual

F r e q u e n c y

16151413121110987654321

20

0

-20

-40

Observation Order

R e s i d u a l

Normal Probability Plot of residuals residual versus Fitted values

Histogram of residuals residual Versus Order of the data

Residual Plots for power

Figure 8 Residual plots of the main and interaction

effects of a 500W stack

Figure 8 shows the residual, histogram, and

probability plots of the data collected, considering

both the main and interaction effects. It can be

inferred from the figure that the data follow the

normal distribution and the interaction effects in the

residual plots are random. The graph effects using

the ANOVA general linear model also show that the

factors C and D are significant compared to A and B,

as shown in Figure 9.

Source

Sum Of

Squares

%

Contributio

n

Degree

s Of

Freedo

m

Mean

Square F P

A 517.5625 2.155707 1 517.5625 49.58683 0.000108

C 16448.06 68.50807 1 16448.06 1575.862 0

D 885.0625 3.686387 1 885.0625 84.79641 0.000016

AC 742.5625 3.092858 1 742.5625 71.14371 0.00003

AD 855.5625 3.563516 1 855.5625 81.97006 0.000018

CD 742.5625 3.092858 1 742.5625 71.14371 0.00003

ACD 885.0625 3.686387 1 885.0625 84.79641 0.000016

ERROR 83.5 8 10.4375



.

1-1

180

165

150

135

120

1-1

1-1

180

165

150

135

120

1-1

A

M e a n

B

C D

Main Effects Plot for powerData Means

1-1 1-1 1-1

200

160

120200

160

120

200

160

120

A

B

C

D

-1

1

A

-1

1

B

-1

1

C

Interaction Plot for powerData Means

.Figure 9 Main and interaction effects of the four

factors at two levels on the fuel cell stack

performance

The model equation can be written after

inclusion of interaction effects as

)( X*)( X*( A D / 2 )

+)( X*( D / 2 )+)( X*( C / 2 )+)( X*( A / 2 )+5 2 . 4 3 7 51

41

431

^

=Y

Here estimated power is calculated from the model

using three significant terms A, C and D. X1, X3 and

X4 are levels of the factors A, C and D corresponding

to experiments.

This model accounts for 99.6% variation

and also one can see that the main interaction

contributor arises from the C and D factors, which

are Flow rate of the Hydrogen and the flow rate of

oxygen.

Present experimental data of voltage current

characteristics is compared with the experimental

data of K.S.Dathatreyan et al. [19] and is shown in

Figure 10. It shows the good agreement with the data

of K.S.Dathatreyan et al. for the fuel cell stack with

electrode area of 100 cm2 with 9 cell stack.

current density, mA/cm2

0 20 40 60 80 100 120 140 160

s

t a c k p o t e n t i a l , V o l t s

4

6

8

10

12

14

16

18

20

ExperimentalElectrode Area - 100cm

2

stack size=20cells

K.S. Dhathathreyan et al.

Electrode Area - 100cm2

Figure 10 Comparison of voltage current

Characteristics of experimental data with

K.S.Dhatatreyan et al .

4. Conclusions

The Design of experiment methodology with its

statistical techniques is then well-suited to analyse

the tests conducted on Fuel cells. Indeed, the DOEmethodology offers a wide range of practical tools,

graphical representations and techniques that can be

suitable mediums for FC experimenters and

developers. The DOE approach leads to simple and

precise models which highlight the impacts of the

factors on the response and detect possible

interactions between parameters. Factorial method

has been applied to the 500W PEMFC stack for

statistical sensitivity analysis. The conditions for operating the stack with respect to pressure and flow

rate of the reactants were identified by design of

experiments method. The effects of interactions

among the various factors at two different levels werealso identified along with the major contributor by

sensitivity analysis by statistical methods. From the

experiments and statistical analysis method, it has

been observed that Hydrogen flow plays a major rolefor getting the maximum performance from the fuel

cell stack and this has got a physical significance in

terms of water removal and un reacted nitrogen

blanket removal from the reaction site. In the

fractional factorial experiments the number of

experiments was reduced, also showed the same

results revealing that fractional factorial experiments

can be applied for getting the major contributor

among the various variables for fuel cell stack performance with respect to obtaining maximum

power. It is also observed that the number of

experiments can be reduced to evaluate the

robustness of the stack with respect to operating

conditions, thereby saving time and materials. It is

also observed that the experimental design

methodology is a suitable tool for the improvement

of fuel cell systems.



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Documents

Sensitivity Analysis of a 500 W Proton Exchange Membrane Fuel Cell Stack by Design of Experiments