Study on LPG Air Fuel Ratio Based on Improved Subtractive Clustering RBF Neural Networks

Abstract:

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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 et al., "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:

$35.00

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