中文摘要：

文章针对纯电动中型客车传动系参数优化问题，以传动系中变速器的传动比为优化变量，以车辆动力性和经济性为优化目标，采用模型在环优化（non-optimization with model in loop，OML）方法，利用Simscape物理建模工具建立电动客车模型，结合带精英策略的非支配排序遗传算法（non-dominated sorting genetic algorithm NSGA-II）对纯电动客车传动系参数进行优化，并基于最小二乘法组合赋权法进行Pareto解集选优确定出最优解。优化结果表明，利用OML方法在约束条件范围内合理地优化了变速器的传动比，加速时间和比能耗分别降低了6％和3．9％，达到了整车动力性和经济性协同优化的目的，为实车开发提供了理论参考。

英文摘要：

For the problems of middle-size electric bus drive-train parameters optimization, an optimization with model in loop（OML） was applied to optimizing the drive-train parameters. In this method, transmission ratio was chosen as optimization variables, and vehicle dynamics along with economy performances were chosen as optimization objectives simultaneously. Simscape physical modeling tool was used to build electric bus model, and the non-dominated sorting genetic algorithm Ⅱ （NSGA- Ⅱ ） was employed for the optimization. Then the final optimal solution was obtained using Pareto selection based on least squares method combining with coefficient weights. The optimization results show that OML can reasonably optimize the transmission ratio within the constraints ranges. The acceleration time and specific energy consumption decreased by 6% and 3. 9% respectively. Therefore, this optimization method can achieve the collaborative optimization, and provide a theoretical reference for the real vehicle development.