Intelligent Electric Vehicle Trajectory Optimization Method Based on Improved Genetic Algorithm

被引:0
作者
Li Aijuan [1 ]
Zhao Wanzhong [2 ]
Qiu Xuyun [1 ]
Wang Xibo [1 ]
Huang Xin [1 ]
Wang Baoyi [1 ]
机构
[1] Shan Dong Jiaotong Univ, Changqing Univ, Haitang Rd 5001,Sci Pk, Jinan 250357, Shandong, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Energy & Power Engn Coll, Nanjing 210016, Jiangsu, Peoples R China
来源
JOINT INTERNATIONAL CONFERENCE ON ENERGY, ECOLOGY AND ENVIRONMENT ICEEE 2018 AND ELECTRIC AND INTELLIGENT VEHICLES ICEIV 2018 | 2018年
基金
中国国家自然科学基金;
关键词
intelligent electric vehicle; trajectory optimization; improved genetic algorithm;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The trajectory planning method for electric vehicle in complex dynamic obstacle environment is an important research of electric vehicle intelligent auxiliary driving technology. In order to make the electric vehicle can run steadily under the high speed driving working condition. An improved genetic algorithm based trajectory planning method was introduced to optimize the generated trajectory. First, the seven times polynomial curve is used to generated trajectory. Then, the improved genetic algorithm is used to optimize the parameters of seven times polynomial curve to make the parameterized trajectory satisfy the dynamic constraints. The real vehicle test results showed that the improved generic algorithm trajectory parameters' variance is reduced greatly and the improved generic algorithm trajectory length is shorter than the traditional generic algorithm. The improved generic algorithm trajectory can satisfy the dynamic constraints better than the traditional generic algorithm trajectory, the optimized effect is effectively and the global optimal solution of the trajectory can be generated using the improved generic algorithm, the vehicle can steering steadily under high speed driving working condition.
引用
收藏
页数:4
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