Application of ANN to Predict S.I. Engine Performance and Emission Characteristics Fuelled Bioethanol
The performance of artificial neural network (ANN) to predict spark ignition (S.I) engine performance such as torque, BSFC, exhaust temperature and emissions (CO and HC) for various compression ratios was investigated.For training and testing the ANN, experimental data from a single cylinder Hydr...
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| Main Authors: | , , |
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| Format: | E-Article |
| Language: | English |
| Published: |
Trans Tech Publications, Switzerland
2014
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/13919/1/Application%20of%20ANN%20to%20Predict%20S.I.%20Engine%20Performance%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/13919/ http://www.scientific.net/AMM.554.454 |
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| Institution: | Universiti Malaysia Sarawak |
| Language: | English |
| Summary: | The performance of artificial neural network (ANN) to predict spark ignition (S.I) engine
performance such as torque, BSFC, exhaust temperature and emissions (CO and HC) for various
compression ratios was investigated.For training and testing the ANN, experimental data from a
single cylinder Hydra spark ignition engine powered by various bioethanol and gasoline blends (E0,
E10, E20, E40 and E60) were used. ANN performance was measured by mean squared errors and
correlation coefficient. The training function used was trainbr and the training algorithm used was
feed-forward back propagation. The overall correlation coefficient obtained from the prediction was
0.98526 and the mean squared error obtained was very low (9.26E-06). |
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