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Emissions Prediction of CNG/Diesel Dual Fuel Engine Based on RBF Neural Network
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Technical Paper
2004-01-0646
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Compressed Natural Gas (CNG)/diesel Dual Fuel Engine(DFE) was one of the best choices for solving energy crisis and environment pollution. In order to study and improve the emission performance of the CNG/diesel DFE, an emission model by means of Radial Basis Function neural network was established. The model identified as a black box model with input-output training data didn't require priori knowledge. There were 100 group experimental data over the operation conditions from low load and low rotate speed to heavy load and high rotate speed using for training the neural network, and 20 group test data using for verifying the model.
The study results showed that the predicted results were good agreement with the experimental data. This proves that the developed emission model can be used to successfully predict and optimize the emission performance of DFE.
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Authors
Citation
Liu, Z. and Fei, S., "Emissions Prediction of CNG/Diesel Dual Fuel Engine Based on RBF Neural NetworkAlso In
References
- Liu, Zhentao 2000 A Study of Combustion and Control Model of Natural Gas -Diesel Fuel Engine by means of Neural Network Zhejiang University China
- YAN, Zhao-da ZHOU, Chong-guang SU, Shi-chuan LIU, Zhen-tao WANG, Xi -zhen 2003 Application of neural network in the study of combustion rate of natural gas/diesel dual fuel engine Journal of Zhejiang University SCIENCE 4 2 170 174
- FEI, Shao-mei LIU, Zhen-tao YAN, Zhao-da 2003 Knock prediction for dual fuel engines by using a simplified combustion model Journal of Zhejiang University SCIENCE 4 5 591 594
- Yan, Zhaoda Kriam, G.A. 1992 A predictive model for dual fuel D. I diesel Engine performance and Emission ASME 27 33 39
- Zhou, B. Tan, D.M. Wei, D.Y. 2001 Prediction of the Emissions from internal combustion engine using a neural network CSICE 4 361 364
- Korres, D.M. Anastopoulos, G. Lois, E. Alexandridis, A. Sarimveis, H. Bafas, D. A neural network approach to the prediction of diesel fuel lubricity Fuel 81 2002 1243 1250
- Ilkivová, M.R. Ilkiá, B.R. Neuschl, T. 2002 Comparison of a linear and nonlinear approach to engine misfire detection Control Engineering Practice 10 2002 1141 1146
- Inoue Kaoru Iiguni Youji Maeda Hajime 2003 Image restoration using the RBF network with variable regularization parameters Neurocomputing 50 2003 177 191
- Omatu, S. Khalid, M. 1996 Neuro-control and its Applications Springer-Verlag London Limited