基于粒子群算法纯电动汽车传统优化设计  

Optimization Design of Pure Electric Vehicle Transmission System Based on Particle Swarm Optimization

作　　者：吉协福 刘祚时[1] JI Xie-fu;LIU Zuo-shi(Mechanical and Electrical Engineering,Jiangxi University of Science and Technology,Jiangxi Ganzhou 341000,China)

机构地区：[1]江西理工大学机电工程学院,江西赣州341000

出　　处：《机械设计与制造》2022年第5期60-63,68,共5页Machinery Design & Manufacture

基　　金：国家自然科学基金(71361014);江西省研究生创新专项资金资助项目(YC2018-S325)。

摘　　要：为了纯电动汽车更好适应城市路况,获得更好的动力性和经济性,以某型单挡的纯电动汽车为研究对象,在基于整车设计参数和动力性能参数上,合理匹配两挡AMT变速器。以加速时间最短和百公里能耗最少为优化目标,以整车动力性、能量消耗和传动系统速比为约束条件,搭建Matlab/Simulink与Isight联合仿真模型。采用粒子群算法对传动系统速比进行优化,优化后仿真结果表明:在NEDC循环工况下,百公里能量消耗降低了2.6%,(0~100)km/h加速时间缩短了4.7%,并进行实车试验,验证仿真合理性。In order to better adapt to the urban road conditions and obtain better power and economy,the pure electric vehicle with a single type is taken as the research object,and the two-shift AMT is reasonably matched based on the vehicle design parameters and dynamic performance parameters. transmission. With the shortest acceleration time and the minimum energy consumption of 100 kilometers as the optimization goal,the Matlab/Simulink and Isight joint simulation model was built with the constraints of vehicle dynamics,energy consumption and transmission system speed ratio. The multi-objective particle swarm optimization algorithm is used to optimize the speed ratio of the two-speed pure electric vehicle transmission system. The simulation results before and after the comparison show that the optimized parameters are reduced by 2.6%,(0~100)km/h under the NEDC cycle conditions. Accelerated time is reduced by 4.7%,and real vehicle test is carried out to verify simulation rationality.

关 键 词：纯电动汽车 传动系统 粒子群算法 优化仿真 

分 类 号：TH16[机械工程—机械制造及自动化] TH12