Energy Procedia 14 (2012) 1427 – 1438

1876-6102 © 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the organizing committee of 2nd International Conference on Advances in Energy Engineering (ICAEE).doi:10.1016/j.egypro.2011.12.887

Available online at www.sciencedirect.com

Energy

Procedia Energy Procedia 00 (2011) 000–000

www.elsevier.com/locate/procedia

Available online at www.sciencedirect.com

Advances in Energy Engineering

Experimental Investigation on Attenuation of Emission with Optimized LPG Jet Induction in a Dual Fuel Diesel Engine

and Prediction by ANN Model

Thomas Renald C.Ja*, Somasundaram Pb a Department of Aeronautical Engineering, Sri Ramakrishna Engineering College, Coimbatore, Tamilnadu, India. bDepartment of Mechanical Engineering, KS Rangasamy College of Technology, Tiruchengode, Tamilnadu, India.

Abstract

Environment pollution due to vehicles exhaust emission is still a severe crisis and an international concern has been raised for its control and diminution. Especially, man-kind is experiencing an epidemic of illnesses made worse by air pollution mainly because of increased number of automotive vehicles. The main problem faced by most of the vehicles today is the emission of NOx which can be controlled by different ways such as exhaust gas recirculation, using alternate fuels, turbo charging, and different mode of combustion. On the other hand, diesel engines are the most trustworthy power sources in the transportation. Due to inflexible emission norms and rapid depletion of petroleum resources, there has been a continuous exertion to use alternative fuels. Further researches are being carried out to reduce emission rates and these researches would be explored till reducing the exhaust emission upto zero level. In such a way, the present investigation explores with a series of experiments towards effective combustion of air, LPG and diesel mixture without encompassing major modification in the engine construction. Here, LPG jet is inducted through air inlet to accomplish homogeneous mixture then it is allowed into the combustion chamber of CI engine. The major parameters of the LPG jet injector are optimised through CFD technique by utilizing a commercial CFD code. Changes in the performance of the engine and emission levels with the influences of the jet parameters are observed and analysed experimentally. The optimized jet parameters obtained through CFD technique and the experimental results achieved from the dual fuelled CI engine show considerable improvement in the engine performance and significant reduction in CO2, CO, HC and NOx emission besides the normal engine performance and emission levels of diesel fuel induction. Eventually, an artificial neural network (ANN) model is developed for predicting the emission levels based on the jet parameters, applying load and % of LPG induction by utilizing the experimental results. It is also found that the predicted results provided good agreement with the experimental results.

© 2011 Published by Elsevier Ltd.

Keywords: Dual fuel CI engine, LPG jet injection, homogeneous air-fuel mixture, jet parameters, CFD approach, reduction of emission, engine performance, ANN model.

* Corresponding author. Tel.: +919894956436. E-mail address: thomsi_reni2000@yahoo.co.in

© 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the organizing committee of 2nd International Conference on Advances in Energy Engineering (ICAEE). Open access under CC BY-NC-ND license.

Open access under CC BY-NC-ND license.

1428 Thomas Renald C.J and Somasundaram P\ / Energy Procedia 14 (2012) 1427 – 1438Author name / Procedia Environmental Sciences 00 (2011) 000–000

1. Introduction

LPG known as an auto gas is a mixture of Propane and Butane. LPG is probably the third largest used fuel after petrol and diesel and is widely used as a cleaner, eco-friendly automotive fuel.

LPG produces significantly less carbon monoxide and oxides of nitrogen emissions as well as a smaller percentage of carbon dioxide emissions. LPG also emits 90% less particulates than diesel engines. Reductions in emissions from LPG have resulted in the government, offering a variety of incentives to encourage motorists to convert to LPG. Car owners driving vehicles using alternative fuels will be taxed less than vehicles using petrol or diesel. Other environmental advantages of Liquid Petroleum Gas as an alternative fuel include the fact that LPG engines are significantly quieter than diesel engines and marginally quieter than petrol engines. Hence there is a scope for designing a gas jet and its position to study the engine performance rate and emission. Gisoo Hyun et al. [1] developed an LPG fuelled direct injection SI engine, especially in order to improve the exhaust emission quality while maintaining high thermal efficiency comparable to a conventional engine through Computational Fluid Dynamics (CFD). Chunhua Zhang et al. [2] conducted a study on the control scheme of a liquefied petroleum gas (LPG)–diesel dual-fuel engine with electronic control. The experimental results showed that comparing with diesel, the output performance of dual fuel is not reduced, while smoke emission of dual fuel is significantly reduced, NOx emission of dual fuel is hardly changed, but HC emission and CO emission of dual fuel are increased and fuel consumption of dual fuel is reduced. Kurniawan et al. [3] used computational fluid dynamics (CFD) simulation and investigated the effect of piston crown shape to air motion characteristics of an internal combustion engine. White et al. [4] used CFD packages Fluent to model the direct-injection of two such fuels simultaneously into an engine and studied about the salient features of the two fuel jets are being to optimize the design of a dual-fuel injector for compression-ignition engines. Roberto et al. [5] examined the flow geometry effects on the turbulent mixing efficiency quantified as the mixture fraction and compared two different flow geometries are at similar Reynolds numbers, Schmidt numbers, and growth rates, with fully developed turbulence conditions. Ren et al. [6] investigated the performances of the gaseous fuel supply and its influence on hydrocarbon (HC) emissions of dual-fuel engines and presented a new design of manifold respirators with mixers. Cao et al. [7] analysed an experiment on engine performance and sprays and characteristics between diesel and mixed liquefied petroleum gas (LPG)/diesel injection engines. The performance test results showed that with LPG the mixed ratio increases, engine power reduces slightly, fuel consumption and engine noise have almost no change, pollutant emissions of smoke, CO and NOx at full load are improved significantly, but the amount of unburned HC increases.

In the above literature survey it has been reviewed that the mixture formation is good by modifying the design of piston head. The performance of the engine increases when the LPG is electronically injected with micro controllers according to the speed and power required. The emissions CO and NOx from the dual fuel engine are greatly reduced. HC emissions from dual fuel engine are par with that of diesel at full load and its less in low loads and half loads. The performance of the engine could be increased by designing the piston head by taking swirl and tumble ratio of the entering air. Studying the flow characteristics and changing the flow pattern shows a significant change in performance of engine. The design of the gaseous fuel supply system has a great influence on HC emissions in dual-fuel engines at light load. A manifold respirator with a mixer gives the best performance in reducing HC emissions compared with a common pipe mixer and a respirator with no mixer. Literature survey confirms that CFD tool can be used to study the gas jet parameters so as to improve performance of the engine and emission. Major problems in emission control are design of engine and improper air-fuel mixture in the combustion system. In an ideal combustion process, air-fuel mixture would be burnt completely within the combustion chamber. In actual, when fuel is burnt, it emits virtually insignificant CO, O2 and relatively little NOx, the main constituents of acid rain, and substantially less CO2, a key culprit in the greenhouse debate, than most oil products and coal.

Thomas Renald C.J and Somasundaram P\ / Energy Procedia 14 (2012) 1427 – 1438 1429Author name / Procedia Environmental Sciences 00 (2011) 000–000

Major techniques can be followed in the reduction of emission problem are, • Modifying the engine design; • Using alternate fuel which produces low emission; • Recirculating or treating the exhaust for further utilization or conversion.

The emission control problems have been addressed in numerous research works, because reduction of emission is a difficult problem which is influenced by design of an engine, appropriate fuel, proper air-fuel ratio and homogeneous mixture, the engine operating parameters include load, speed, compression ratio, pilot fuel injection timing, pilot fuel mass inducted and intake manifold conditions. Finally, it has been found that there is a scope for improving the performance and reducing emission level of diesel engines exclusive of major modification in the engine construction.

Nomenclature d inlet diameter of nozzle in mm

x distance between tip of the nozzle and intersection of vertical axis of air inlet pipe and nozzle axis in mm

θ inclination of nozzle in degree CO2 Carbon Dioxide CO Carbon Monoxide FC Fuel Consumption FHP Frictional horse Power FP Fuel Power HC Hydrocarbons IP Indicated Power in W NOx Nitrogen Oxide O2 Oxygen RPM Revolution per Minute SFC Specific Fuel Consumption ηmech Mechanical Efficiency ηB.TH Brake Thermal efficiency ηI.TH Indicated Thermal Efficiency

2. Problem statement

Recent researches and investigations on the compression ignition (CI) engine performance parameters optimization and emission problems are mainly dealing with modification of engine construction to improve the performance and reduction of emission which is tedious and non-interchangeable. The present study made an attempt on reduction of emission level in the CI engine without having any major alteration in the existing engine construction and also to improve the performance of engine. In the betterment of engine efficiency and reduction of emission level, LPG and air should be mixed homogenously. The main objective of this work is to design a simple and realistic setup which would not disturb the existing engines construction and the developed setup could be adapted to all engines efficiently.

1430 Thomas Renald C.J and Somasundaram P\ / Energy Procedia 14 (2012) 1427 – 1438

3. Method

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Thomas Renald C.J and Somasundaram P\ / Energy Procedia 14 (2012) 1427 – 1438 1431

4. Experim

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1432 Thomas Renald C.J and Somasundaram P\ / Energy Procedia 14 (2012) 1427 – 1438

CASE 4: 60In this c

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5. Results a

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/ Procedia Enviro

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Thomas Renald C.J and Somasundaram P\ / Energy Procedia 14 (2012) 1427 – 1438 1433Author name / Procedia Environmental Sciences 00 (2011) 000–000

5.2 Emission level

The emission results of main toxic gases such as CO, CO2, HC, NOx and amount of O2 are compared

and presented in Figures from 9 to 13 for different loading conditions of 0 kg, 5 kg, 10 kg and 15 kg. Fig. 9 shows the comparison plot of CO %vol for different diesel and LPG fuel ratio with different loading conditions and minimum CO % vol is noted for the case 80% of diesel and 20% of LPG. The comparison plot of CO2 % vol in the exhaust gas for various diesel and LPG fuel ratio with different loading conditions is presented in Fig. 10. From this figure, reduced concentration of CO2 %vol is observed for the case 40% of diesel and 60% of LPG. The level of O2 % vol is compared and shown in Fig. 11 and minimum concentration of O2 % vol is noticed for the case 60% of diesel and 40% of LPG which implies that air/LPG mixture is homogeneous and air-fuels mixture is burnt fully. There is no considerable change in the concentration of HC which can be seen from Fig. 12. Fig. 13 delineates the comparison of concentration level of NOx for various diesel and LPG fuel ratio with different loading conditions and predominant reduction in NOx emission is examined for the case 40% of diesel and 60% of LPG. According to these results, it is obvious that increase in LPG fuel ratio decreases the emission rate considerably.

0

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HC

in p

pm

Load in kg

100% DIESEL 80% DIESEL+20% LPG

60% DIESEL+ 40% LPG 40% DIESEL+60% LPG

Fig. 9 Load Vs. CO Fig.10 Load Vs. CO2

Fig.11 Load Vs. O2 Fig.12 Load Vs. HC

1434 Thomas Renald C.J and Somasundaram P\ / Energy Procedia 14 (2012) 1427 – 1438

From the

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/ Procedia Enviro

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Thomas Renald C.J and Somasundaram P\ / Energy Procedia 14 (2012) 1427 – 1438 1435Author name / Procedia Environmental Sciences 00 (2011) 000–000

In order to predict and optimise the present problem, an ANN based model was developed with the base of feed forward back propagation method. A code was developed based on the feed forward back propagation method by utilizing Matlab R2009a software package. Fig. 14 shows the developed architecture of artificial neural network with five input layer with 5 neurons, seven output layer with 7 neuron and one hidden layer with 10 neurons.

The links with synaptic weights are connected between neurons and the back-propagation training algorithm is based on weight updates so as to minimize the sum of squared error for K-number of output neurons, given as

2.

1. )(

21

pk

K

kpk odE −= ∑

= (1)

where dk,p = desired output for the pth pattern. The weights of the links are updated as

)()()1( njipipjnjinji woww Δ++=+ αηδ (2)

where n is the learning step, η is the learning rate and α is the momentum constant. In equation (4), δpj is the error term, which is given as follows:

For output layer : Kkood kpkpkppk ,....1),1)(( =−−=δ (3)

For hidden layer : Jjwoo kjpkpjpjpj ,....1,)1( =−= ∑ δδ (4)

where J is the number of neurons in the hidden layer. The training process is initialized by assigning small random weight values to all the links. The input–output patterns are presented one by one and updating the weights each time. The mean square error (MSE) at the end of each epoch due to all patterns is computed as

∑ ∑= =

−=NP

p

k

kkpkp od

NPMSE

1 1

2)(1 (5)

where NP =number of training patterns. The training process will be terminated when the specified goal of MSE or maximum number of

epochs is achieved. The activation function for the input and the one hidden layer is chosen as tansigmoidal function. The activation function for the output layer was chosen as pure linear function. The network was then simulated for the input values and a graph is plotted between the output and target (neural network output) values. The network created was trained for the input and output values. The stopping criterion for training was number of epochs and was given as 1000 as shown in Fig.15.

The network was again simulated for the input values and the target values of the experiments conducted. The input values for the test readings were then given and the network was trained. The target value was then obtained and compared with actual outputs. The results were compared with the actual experimental results and the predicted results obtained from the present study show minimal in variations. From Fig. 16, it is clear that the parameters considered could be confidently used for the above method for predicting the emission rates. The behaviours of the parameters are also noted.

The predicted emission levels were compared with the respective experimental results and the absolute percentage error was computed, which is given as

% Absolute error = 100Pr X

alvalueExperimentueedictedvalalvalueExperiment −

(6)

1436 Thomas Renald C.J and Somasundaram P\ / Energy Procedia 14 (2012) 1427 – 1438

Author name / Procedia Environmental Sciences 00 (2011) 000–000

The experimental results of emission levels were utilized for predicting the emission level with the

influences of ‘d’ values, ‘x’ values, ‘θ’ values for different proportions of fuels (Diesel+LPG) with different loading conditions. Both results were compared and shown through Table 1, the absolute percentage error ranges from 0.11498% to 3.28939 % which is in the acceptable range.

7. Conclusions

From all the above results and discussion, the following conclusions are arrived and they are summarized as follows:

• It was found that the new technique which was used in this investigation away from the engine construction influenced on the engine performance and emission levels predominantly.

• The thermal efficiency of the engine increases when powered with dual fuel. The percentage increases about 5% when 60% of diesel and 40% of LPG.

• No considerable change was found in torque and brake mean effective pressure. • The mechanical efficiency was increased about 5% when powered with dual fuel when 60% of

diesel and 40% of LPG. • There was an increase in Hydrocarbon emission when going to dual fuel mode. • Specific fuel consumption was reduced around 33%. • NOx was reduced upto 35% for 60% LPG and 40% diesel proportion when compared to that of

running at 100% diesel. • CO2 emission was reduced about 67% for 60% LPG and 40% diesel proportion. • The CO emission was reduced upto 12% in dual fuel mode for 60% of diesel and 40% of LPG. • The absolute percentage error between experimental and predicted results ranges from 0.11498%

to 3.28939 % which is in the acceptable range. • All these results were obtained for the effective nozzle condition, diameter of 5 mm, x= 10 mm

and θ = 30°. • On the whole, it is recommended that better engine performance and reduced emission level can

be achieved if the dual fuels proportion lies between 40-60 % of diesel and LPG for the nozzle condition, diameter of 5 mm, x= 10 mm and θ = 30°.

Thomas Renald C.J and Somasundaram P\ / Energy Procedia 14 (2012) 1427 – 1438 1437

Table 1 Comparison of experimental results and predicted results of emission levels

Acknowledgement

We are thankful to Kongu Engineering College, Perundurai, Tamilnadu, India, provided laboratory facilities to achieve this work successfully.

References

[1] Gisoo Hyun, Mitsuharu, Sinntchi Goto, (2002). 3-D CFD Analysis of mixture formation process in an LPG DI SI Engine for Heavy Duty Vehicles. International Multidimensional Engine Modeling Users Group Meeting at the SAE Congress, NEDO ( New energy and Industrial Technology Development Organization). National Institute of Advanced Industrial science and Technology.

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-0.0006

18.4

18.51502

0.0063

31

30.99975

8.16E-06

50

49.9976

-0.0000

10 5

90

10 0

100

39

39.4052

-0.01039

287

297.5919

0.03691

0.09

0.09321

-0.0356

2.3

2.2987

-0.0005

17.8

17.52625

-0.015

23

10.53896

0.54178

104

83.8522

-0.1937

12 5

-18

15 0

100

40

39.9821

0.00045

370

369.9996

-9.83E

0.12

0.12966

-0.0804

2.7

2.70053

0.00019

17.3

17.2703

-0.001

22

22.00001

-6.23E 08

124

124.0005

0.000004

5 7 30 0 2

0 80

41

41.0650

-0.00158

194

194.0004

2.23E-06

0.04

0.03991

0.00229

0.9

0.89965

-0.0003

16

16.05588

0.0035

365

364.9999

1.96E-08 1

0.99881

-0.0011

7 7 45 5 2

0 80

42

41.9780

0.00052

230

229.9991

-3.82E

0.04

0.0364

0.09012

1.1

1.10030

0.00027

15.9

15.81117

-0.005

162

162.0003

-1.85E 06

13

13.0019

0.00014

10 7

90

10

20

80

43

42.7587

0.00561

291

291.0016

5.34E-06

0.03

0.03757

-0.2522

1.4

1.40107

0.00077

15.2

15.25564

0.0037

89

89.00038

-4.28E 06

19

18.9997

-0.0000

12 7

-18

15

20

80

43

43.0681

-0.00158

363

362.9998

-6.83E

0.03

0.01451

0.51645

1.8

1.79927

-0.0004

15.9

15.8866

-0.000

55

55.00003

-5.92E 08

46

46.00020

0.000004

5 8 30 0 4

0 60

42

41.9603

0.00095

194

193.9999

-5.33E

0.05

0.05018

-0.0035

0.8

0.80037

0.00046

15.8

15.78135

-0.001

580

580.0003

-4.42E 07

0 0 0

7 8 45 5 4

0 60 

43

42.8352

0.00383

232

231.7513

-0.00107

0.07

0.03434

0.50946

1 0.99352

-0.0064

15.4

15.8822

0.03131

251

263.5828

-0.05013

1 1.64877

0.64877

10 8

90

10

40

60 

43

43.2117

-0.00492

293

292.9991

-2.98E

0.06

0.07156

-0.1927

1.3

1.29966

-0.0002

15.2

15.20409

0.00027

94

93.9997

2.95E-06

10

9.99923

-0.0000

12 8

-18

15

40

60 

44

43.9472

0.00120

369

369.0002

5.81E-07

0.08

0.07791

0.02613

1.6

1.60016

0.00010

15.3

15.29963

-2.4E

58

58.00015

-2.54E 06

19

19.0002

0.000011

5 10

30 0 6

0 40

40

40.0004

-8.92E 06

190

189.9999

-1.06E

0.09

0.09293

-0.0325

0.6

0.60199

0.00331

16.7

1.65E+01

-0.009

15

15.40084

-5.416E

0 0 0

7 10

45 5 6

0 40 

41

40.8627

0.00335

228

230.2618

0.00992

0.1

0.09425

0.057553

0.9

0.91241

0.01379

16

1.60E+01

-0.002

15

14.80828

0.0193194

0 0 0

10

10

90

10

60

40 

42

41.5945

0.00966

285

302.8205

0.06253

0.04

0.04093

-0.0232

1.1

1.20716

0.097415

15.4

15.29654

-0.006

14

15.6648

-0.05133

8 8.32424

0.040530

12

10

-18

15

60

40 

42

41.9994

1.54E-05

363

363.0001

2.73E-08

0.02

0.02224

-0.1117

1.4

1.30374

-0.0687

15.1

15.2365

0.00904

14

14.70005

-2.83E 06

12

12.00088

0.000074

% Absolute error 0.03975

0.67676

3.28939

0.23899

0.11498

2.872407

3.090`984

1438 Thomas Renald C.J and Somasundaram P\ / Energy Procedia 14 (2012) 1427 – 1438 Author name / Energy Procedia 00 (2011) 000–000 12

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