Paper Title:
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.

  Info
Periodical
Advanced Materials Research (Volumes 301-303)
Chapter
Chapter 3: Mechanical, Electronic and Material Engineering
Edited by
Riza Esa and Yanwen Wu
Pages
1789-1794
DOI
10.4028/www.scientific.net/AMR.301-303.1789
Citation
S. B. Yang, M. J. Hu, "Forecasting EGR Rate of Diesel Engine Based on Neural Syncretic Theory", Advanced Materials Research, Vols. 301-303, pp. 1789-1794, 2011
Online since
July 2011
Export
Price
$32.00
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