Forecasting EGR Rate of Diesel Engine Based on Neural Syncretic Theory

Autor: Ming Jiang Hu, Shi Bin Yang
Rok vydání: 2011
Předmět:
Zdroj: Advanced Materials Research. :1789-1794
ISSN: 1662-8985
DOI: 10.4028/www.scientific.net/amr.301-303.1789
Popis: 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.
Databáze: OpenAIRE