Forecasting EGR Rate of Diesel Engine Based on Neural Syncretic Theory

Shi Bin Yang; Ming Jiang Hu

doi:10.4028/www.scientific.net/AMR.301-303.1789

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 301-303Forecasting EGR Rate of Diesel Engine Based on...

Forecasting EGR Rate of Diesel Engine Based on Neural Syncretic Theory

Abstract:

To counter the influencing emission of the diesel engine by the EGR rate, the emission model of the diesel engine was set up by combining Radial Basis Function neural network with Adaptive Neural Fuzzy Inference System. The model first draws on the nonlinear approaching capacity of the RBF network to forecast the diesel engine emission which takes no account of the factor of the EGR rate, and then, based on influencing the diesel engine emission by the EGR rate, the ANFIS system was used to modify the results of the diesel engine emission obtained by using the RBF network so as to acquire the EGR rate curve. The result showed that the emission model of the diesel engine was reasonable; the forecasting strategy had the good resolving power and could be much fitted for the on-line aging forecast of the EGR rate.

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Periodical:

Advanced Materials Research (Volumes 301-303)

Pages:

1789-1794

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.301-303.1789

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Online since:

July 2011

Authors:

Shi Bin Yang, Ming Jiang Hu

Keywords:

Diesel Engine, EGR Rate, Neural Syncretic Theory, On-Line Forecast

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