中国机械工程

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电动汽车动力系统参数多指标稳健设计方法

于丽敏1;熊会元1,2;宗志坚1,2;吴义忠3   

  1. 1.中山大学,广州,510006
    2.东莞中山大学研究院,东莞,523808
    3.华中科技大学,武汉,430074
  • 出版日期:2016-10-25 发布日期:2016-10-21
  • 基金资助:
    国家自然科学基金资助项目(51575205);广东省重大科技专项(2016B010118001);东莞市重大科技项目(201521511902) 

Multi-objective Robust Design of Electric Vehicle Powertrain Parameters

Yu Limin1;Xiong Huiyuan1,2 ;Zong Zhijian1,2;Wu Yizhong3   

  1. 1.Sun Yat-Sen University,Guangzhou,510006
    2.Institute of Dongguan-Sun Yat-Sen University,Dongguan,Guangdong,523808
    3.Huazhong University of Science and Technology,Wuhan, 430074
  • Online:2016-10-25 Published:2016-10-21
  • Supported by:

摘要: 为降低行驶工况的波动对整车经济性能的影响,提出基于多因素行驶工况的动力系统部件参数多指标稳健设计方法。以工况能耗、工况续驶里程和部件成本建立综合经济性能指标函数,以电池、电机和传动系参数为控制因子,以行驶工况的关键因素作为噪声因子,建立动力系统参数稳健设计的数学模型。基于Modelica建立整车性能仿真模型,并构建工况仿真的径向基函数响应面模型。采用概率方法描述行驶工况的不确定性,制订试验设计方案对动力系统参数进行稳健设计。以EVBus进行实例计算,基于蒙特卡罗分析表明稳健设计方案的综合性能指标函数的均值及方差均得到有效改善,表明了研究方法的有效性。

关键词: 电动汽车, 稳健设计, 行驶工况;径向基函数

Abstract: In order to reduce the influences of dynamic driving cycle on economy performance, a multi-objective robust design method for electric vehicle powertrain parameters was presented based on multi-factor driving cycle. With cycle energy consumption, cycle driving range and component cost as comprehensive economy function objectives, battery, motor and transmission parameters as design factors, driving cycle as noise factors, a robust design model for powertrain parameters was proposed, and vehicle performance simulation model was built based on Modelica. A response surface model of cycle simulation was built based on radial basis functions. The uncertainty description of driving cycle was based on probability theory, the design of experiments was carried out to solve the problem. Taking EVBus for example, simulation results show that the means and variances of the comprehensive economy function objectives are improved effectively based on Monte Carlo analysis, which proves the effectiveness of the method.

Key words: electric vehicle, robust design, driving cycle, radial basis function(RBF)

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