The shift system of Automated Mechanical Transmission based on neural network control

被引：0
|
作者：
Lu Zeng [1 ,2 ]
Jun Liu [3 ]
Yong Qin [3 ]
Wang ZiYang [3 ]
机构：
[1] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China
[2] Jiangxi Univ Sci & Technol, Dept Informat Engn, Ganzhou, Jiangxi, Peoples R China
[3] Beijing Jiaotong Univ, Beijing, Peoples R China
来源：
2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2014年
关键词：
automated mechanical transmission; neural network; optimizing shift; clutch engagement;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Automated mechanical transmission technology is very suitable for the development of China's automobile industry realities. The paper discusses optimizing shift regularity of AMT and training simulation of data is completed by neural network. It indicated that distinguish measure of RBF neural network can solve the problem of shift recognition, and offer the shift control strategy of neural network. The research of the paper provides theory basis for improving design and practical application.
引用
收藏
页码：4072 / 4075
页数：4
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