Automobile Transmission Shift Control Based on MMAS and BP Networks

Jianxue Chen

Abstract


The neural network control model of automobile automatic transmission has been developed, which make the optimum shift decision based on the vehicle velocity, the vehicle acceleration and the throttle opening. The MAX-MIN ant syste (MMAS) is introduced to train the neural network weights and thresholds. The basic theory and steps of MMAS algorithm are given, and applied in the automatic transmission shift control. Experimental results show that the automatic transmission shift control system based on MMAS, comparing to the system based on ACO-BP, has better capability of gear recognition, and can make shift decision promptly and effectively.


DOI: http://dx.doi.org/10.11591/telkomnika.v11i8.2417


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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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