基于多目标优化的纯电动车动力系统参数匹配方法  

A Parameter Matching Method for the Powertrain of Battery Electric Vehicle Based on Multi-objective Optimization

作　　者：张抗抗[1] 徐梁飞[1] 华剑锋[1] 李建秋[1] 欧阳明高[1] 赵小羽 成艾国 

机构地区：[1]清华大学汽车安全与节能国家重点实验室,北京100084 [2]上汽通用五菱股份有限公司,柳州545000

出　　处：《汽车工程》2015年第7期757-765,共9页Automotive Engineering

基　　金：科技部国际科技合作计划(2010DFA72760);国家863计划项目(2011AA11A215);上汽通用五菱汽车股份有限公司课题(SGMW5027XYZBF纯电动汽车开发试制及调试)资助

摘　　要：本文提出一种基于多目标优化的纯电动车动力系统的参数匹配方法。该方法以最高车速、加速时间和100km电耗等多个整车性能指标作为优化目标,以传动比为优化变量建立参数匹配优化模型;再以该车型的最基本性能指标作为约束条件得到传动比的可行域,在可行域中采用多目标遗传算法对优化问题进行求解;求出固定传动比变速器和两挡变速器两种情况下的Pareto最优解集,作为备选方案集;综合对比不同电机的备选方案集,确定最终的参数匹配方案,并进行样车的开发。转鼓试验结果表明,所开发车辆达到设计的性能指标,验证了所提出的参数匹配方法的有效性。A parameter matching method for the power system of battery electric vehicle based on multi-ob- jective optimization is presented in this paper. An optimization model for parameter matching is set up with several vehicle performance indicators including maximum speed, acceleration time and electricity consumption per 100 km as optimization objectives, and with gear ratios as optimization variables. Then the feasible region of gear ratio is ob- tained with the most basic performance indicators as constraints and multi-objective genetic algorithm is adopted to find the optimization solutions in feasible region, and the Pareto optimal solution set is solved out as optional variant set for both transmission with fixed gear ratio and two-gear transmission. Finally the parameter matching variant is determined by comprehensively comparing optional variant set, with prototype vehicle developed. The results of ro- tary drum test show that the vehicle developed achieves the designed performance indicators, verifying the effective- ness of the parameter matching method presented.

关 键 词：纯电动车 PARETO最优解集 参数匹配 多目标优化 遗传算法 

分 类 号：U469.72[机械工程—车辆工程]