Automotive Innovation ›› 2019, Vol. 2 ›› Issue (4): 254-262.doi: 10.1007/s42154-019-00079-9

• • 上一篇    下一篇

Comprehensive Analysis and Optimization of Dynamic Vibration-Absorbing Structures for Electric Vehicles Driven by In-Wheel Motors

Yechen Qin1, 4, Zhenfeng Wang2, Kang Yuan3, Yubiao Zhang4   

  1. 1.Beijing Institute of Technology, Beijing, China
    2.China Automotive Engineering Research Institute Co Ltd., Tianjin, China
    3.Chongqing University, Chongqing, China
    4.University of Waterloo, Waterloo, Canada

  • 出版日期:2019-12-17 发布日期:2019-12-17
  • 通讯作者: Yechen Qin https://orcid.org/0000-0003-1928-0113 E-mail:qinyechenbit@gmail.com

Comprehensive Analysis and Optimization of Dynamic Vibration-Absorbing Structures for Electric Vehicles Driven by In-Wheel Motors

Yechen Qin1, 4, Zhenfeng Wang2, Kang Yuan3, Yubiao Zhang4#br#   

  1. 1.Beijing Institute of Technology, Beijing, China
    2.China Automotive Engineering Research Institute Co Ltd., Tianjin, China
    3.Chongqing University, Chongqing, China
    4.University of Waterloo, Waterloo, Canada
  • Online:2019-12-17 Published:2019-12-17
  • Contact: Yechen Qin https://orcid.org/0000-0003-1928-0113 E-mail:qinyechenbit@gmail.com

摘要: Distributed-drive electric vehicles (EVs) replace internal combustion engine with multiple motors, and the novel configuration results in new dynamic-related issues. This paper studies the coupling effects between the parameters and responses of dynamic vibration-absorbing structures (DVAS) for EVs driven by in-wheel motors (IWM). Firstly, a DVAS-based quarter suspension model is developed for distributed-drive EVs, from which nine parameters and five responses are selected for the coupling effect analysis. A two-stage global sensitivity analysis is then utilized to investigate the effect of each parameter on the responses. The control of the system is then converted into a multiobjective optimization problem with the defined system parameters being the optimization variables, and three dynamic limitations regarding both motor and suspension subsystems are taken as the constraints. A particle swarm optimization approach is then used to either improve ride comfort or mitigate IWM vibration, and two optimized parameter sets for these two objects are provided at last. Simulation results provide in-depth conclusions for the coupling effects between parameters and responses, as well as a guideline on how to design system parameters for contradictory objectives. It can be concluded that either passenger comfort or motor lifespan can be reduced up to 36% and 15% by properly changing the IWM suspension system parameters.

关键词: Global sensitivity analysis, IWM suspension, Parameter optimization, Electric vehicle ,

Abstract: Distributed-drive electric vehicles (EVs) replace internal combustion engine with multiple motors, and the novel configuration results in new dynamic-related issues. This paper studies the coupling effects between the parameters and responses of dynamic vibration-absorbing structures (DVAS) for EVs driven by in-wheel motors (IWM). Firstly, a DVAS-based quarter suspension model is developed for distributed-drive EVs, from which nine parameters and five responses are selected for the coupling effect analysis. A two-stage global sensitivity analysis is then utilized to investigate the effect of each parameter on the responses. The control of the system is then converted into a multiobjective optimization problem with the defined system parameters being the optimization variables, and three dynamic limitations regarding both motor and suspension subsystems are taken as the constraints. A particle swarm optimization approach is then used to either improve ride comfort or mitigate IWM vibration, and two optimized parameter sets for these two objects are provided at last. Simulation results provide in-depth conclusions for the coupling effects between parameters and responses, as well as a guideline on how to design system parameters for contradictory objectives. It can be concluded that either passenger comfort or motor lifespan can be reduced up to 36% and 15% by properly changing the IWM suspension system parameters.

Key words: Global sensitivity analysis, IWM suspension, Parameter optimization, Electric vehicle ,