多目标遗传算法的纯电动汽车动力系统参数优化

以某款新开发的两挡机械式自动变速器(Automatic Mechanical Transmission,AMT)纯电动汽车作为研究样本,为兼顾纯电动汽车整车经济性和动力性需求,提出一种动力系统参数优化方案。以0~100 km/h加速时间、新标欧洲循环测试(New European Driving Cycle,NEDC)工况整车百公里能量消耗和一挡最大爬坡度为优化目标,将动力性以及变速器速比约束等指标作为约束条件,借助Isight多学科设计优化软件和Cruise软件建立集成优化模型,并选择带精英策略的快速非支配排序遗传算法对动力系统速比进行多目标优化。优化结果表明,速比优化后的目标车型整车经济性提升了3.19%,最高车速提高了17.55%,虽然0~100 km/h加速时间增加了0.53%,一挡最大爬坡度降低了13.15%,但整车性能更符合所期望的设计目标。

Parametric optimization of pure electric vehicle powertrain based on multi-objective genetic algorithm

Taking a newly developed two-speed Automatic Mechanical Transmission(AMT)pure electric vehicle as the research model,a powertrain parameter optimization scheme was proposed to meet the demand of economy and dynamic performance of pure electric vehicle.Taking the 0~100 km/h acceleration time,100-kilometer energy consumption in New European Driving Cycle(NEDC)and first gear maximum climbing angle as the optimization target,the dynamic performance and transmission ratio constraints were used as constraints.The integrated optimization model was established by Isight multidisciplinary design optimization software and Cruise software,and a fast non-dominated sorting genetic algorithm with elite strategy was selected for multi-objective optimization of transmission ratio.The results show that the economic performance of the target model after the optimization of the transmission ratio is increased by 3.19%,and the maximum speed is increased by 17.55%.Although the 0~100 km/h acceleration time is increased by 0.53%and the maximum climbing performance of the first gear is decreased by 13.15%,the overall vehicle performance is more in line with the desired design objectives.