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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2003, Vol. 4 Issue (2): 170-174    DOI: 10.1631/jzus.2003.0170
Energy Engineering     
Application of neural network in the study of combustion rate of natural gas/diesel dual fuel engine
YAN Zhao-da, ZHOU Chong-guang, SU Shi-chuan, LIU Zhen-tao, WANG Xi-zhen
Department of Energy Engineering, Zhejiang University, Hangzhou 310027, China
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Abstract  In order to predict and improve the performance of natural gas/diesel dual fuel engine (DFE), a combustion rate model based on forward neural network was built to study the combustion process of the DFE. The effect of the operating parameters on combustion rate was also studied by means of this model. The study showed that the predicted results were good agreement with the experimental data. It was proved that the developed combustion rate model could be used to successfully predict and optimize the combustion process of dual fuel engine.

Key words： Dual fuel engine      Forward neural network      Rate of combustion     
Received: 28 February 2002     
CLC:  TK411.2  
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ZHOU Chong-guang
YAN Zhao-da
SU Shi-chuan
LIU Zhen-tao
WANG Xi-zhen
Cite this article:

YAN Zhao-da, ZHOU Chong-guang, SU Shi-chuan, LIU Zhen-tao, WANG Xi-zhen. Application of neural network in the study of combustion rate of natural gas/diesel dual fuel engine. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2003, 4(2): 170-174.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2003.0170     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2003/V4/I2/170

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[2] FEI Shao-mei, LIU Zhen-tao, YAN Zhao-da. Knock prediction for dual fuel engines by using a simplified combustion model[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2003, 4(5): 591-594.
[3] LIU Ping, CHENG Yi-yu. AN IMPROVED GENETIC ALGORITHM FOR TRAINING LAYERED FEEDFORWARD NEURAL NETWORKS[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2000, 1(3): 322-326.