Paper Title:
Study on LPG Air Fuel Ratio Based on Improved Subtractive Clustering RBF Neural Networks
  Abstract

The paper refers to the mathematical model of gasoline engine, and builds liquid-jet LPG(Liquefied Petroleum Gas) engine model. Based on the model, when the specific of the parameters distribution of operating engine are known, RBF neural network can estimate center value and the number of hidden layers precisely, and control engine A/F in fine range. But the parameter features of operating engine are unknown in advance. The paper provides a improved subtractive clustering - RBF neural Networks algorithm to control A/F of LPG engine. Simulation shows, improved subtractive clustering can precisely determine the number of neuron of RBF neural network hidden layers under unknown operation parameters, and the precision is higher, and self-study and adaptive adjusting is better than before.

  Info
Periodical
Key Engineering Materials (Volumes 474-476)
Edited by
Garry Zhu
Pages
1122-1127
DOI
10.4028/www.scientific.net/KEM.474-476.1122
Citation
Y. M. Lin, Z. P. Feng, H. F. Guan, "Study on LPG Air Fuel Ratio Based on Improved Subtractive Clustering RBF Neural Networks", Key Engineering Materials, Vols. 474-476, pp. 1122-1127, 2011
Online since
April 2011
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Price
$32.00
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Authors: Long Wu, Jian Jun Liu
Chapter 1: Mechatronics, Robotics and Control Systems
Abstract:Due to engine performance, fuel economy and emission performance are closely related with its transient air-fuel ratio, so the research of...
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