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Vertical-Longitudinal Coupling Effect Investigation and System Optimization for a Suspension-In-Wheel-Motor System in Electric Vehicle Applications

Author

Listed:
  • Ze Zhao

    (National Engineering Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Lei Zhang

    (National Engineering Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Jianyang Wu

    (Beijing Institute of Space Launch Technology, Beijing 100076, China)

  • Liang Gu

    (National Engineering Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Shaohua Li

    (State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures, Shijiazhuang Tiedao University, Shijiazhuang 050043, China)

Abstract

In-wheel-motor-drive electric vehicles have attracted enormous attention due to its potentials of improving vehicle performance and safety. Road surface roughness results in forced vibration of in-wheel-motor (IWM) and thus aggravates the unbalanced electric magnetic force (UEMF) between its rotor and stator. This can further compromise vertical and longitudinal vehicle dynamics. This paper presents a comprehensive study to reveal the coupled vertical–longitudinal effect on suspension-in-wheel-motor systems (SIWMS) along with a viable optimization procedure to improve ride comfort and handling performance. First, a UEMF model is established to analyze the mechanical–electrical–magnetic coupling relationship inside an IWM. Then a road–tire–ring force (RTR) model that can capture the transient tire–road contact patch and tire belt deformation is established to accurately describe the road–tire and tire–rotor forces. The UEMF and the RTRF model are incorporated into the quarter-SIWMS model to investigate the coupled vertical–longitudinal vehicle dynamics. Through simulation studies, a comprehensive evaluation system is put forward to quantitatively assess the effects during braking maneuvers under various road conditions. The key parameters of the SIWMS are optimized via a multi-optimization method to reduce the adverse impact of UEMF. Finally, the multi-optimization method is validated in a virtual prototype which contains a high-fidelity multi-body model. The results show that the longitudinal acceleration fluctuation rate and the slip ratio signal-to-noise ratio are reduced by 5.07% and 6.13%, respectively, while the UEMF in the vertical and longitudinal directions varies from 22.2% to 34.7%, respectively, and is reduced after optimization. Thus, the negative coupling effects of UEMF are minimized while improving the ride comfort and handling performance.

Suggested Citation

  • Ze Zhao & Lei Zhang & Jianyang Wu & Liang Gu & Shaohua Li, 2023. "Vertical-Longitudinal Coupling Effect Investigation and System Optimization for a Suspension-In-Wheel-Motor System in Electric Vehicle Applications," Sustainability, MDPI, vol. 15(5), pages 1-24, February.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4168-:d:1080374
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    References listed on IDEAS

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    1. Li, Jian & Cho, Yunhyun, 2010. "Dynamic reduction of unbalanced magnetic force and vibration in switched reluctance motor by the parallel paths in windings," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(2), pages 407-419.
    2. Jian Wu & Shuo Cheng & Binhao Liu & Congzhi Liu, 2017. "A Human-Machine-Cooperative-Driving Controller Based on AFS and DYC for Vehicle Dynamic Stability," Energies, MDPI, vol. 10(11), pages 1-18, October.
    3. Zhang, Junjiang & Yang, Yang & Hu, Minghui & Yang, Zhong & Fu, Chunyun, 2021. "Longitudinal–vertical comprehensive control for four-wheel drive pure electric vehicle considering energy recovery and ride comfort," Energy, Elsevier, vol. 236(C).
    4. Tao Li & Shuo Zhang & Gang Xiao & Minqi Wang & Hanwen Zhong & Jianghua Feng, 2022. "Brake Instability Dynamic Model and Active Control Strategy for a Multiunit Articulated Rubber-Wheel Autonomous Rail Rapid Transit System," Sustainability, MDPI, vol. 14(21), pages 1-21, November.
    5. Zhenpo Wang & Yachao Wang & Lei Zhang & Mingchun Liu, 2017. "Vehicle Stability Enhancement through Hierarchical Control for a Four-Wheel-Independently-Actuated Electric Vehicle," Energies, MDPI, vol. 10(7), pages 1-18, July.
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