Comprehensive Performance Optimization for Electric Vehicles equipped with AMT based on Genetic Algorithm

被引：0
|
作者：
Yin, Xiaofeng [1 ]
Pickert, Volker [2 ]
Wu, Xiaohua [1 ]
Sun, Hua [1 ]
Li, Wei [1 ]
机构：
[1] Xihua Univ, Chengdu, Peoples R China
[2] Newcastle Univ, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England
来源：
2015 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE AND EXPO (ITEC) | 2015年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
To optimize the comprehensive performance of electric vehicles (EVs) equipped with automated manual transmission (AMT), a performance evaluation function that takes into account dynamic performance, economic performance and driver's driving intentions is put forward. The approach proposed in this paper is based on a gearshift schedule optimization method based on genetic algorithm (GA) using the evaluation function as objective, the accelerator pedal position and velocity as design variables, and using motor efficiency to narrow solution space. Five gearshift schedules representing different driver's intentions have been developed for a 3-speed AMT. Simulation results show that the proposed GA-based optimization method can improve the comprehensive performance of EV equiped with AMT effectively.
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页数：5
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