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To improve the vibration isolation performance of the hub motor driven vehicles (HMDV) under adverse vibration, this study presents a structural design for a suspension system. Firstly, a quarter HMDV model is developed under the effects of unbalanced radial forces of the switched reluctance motor (SRM) and random road excitation. Based on the analogy between mechanical and electrical networks, two configurations of inertial suspension systems (ISS) are subsequently proposed. The Particle Swarm Optimization (PSO) algorithm is employed to optimize the suspension parameters, aiming to minimize the root mean square (RMS) values of body acceleration (azs), suspension working space (zSWS), and dynamic tyre load (FDTL). Finally, numerical simulations are carried out in the MATLAB/Simulink environment. The results showed that the ISS significantly improves vibration performance compared with the conventional suspension system (ST0). In particular, the ISS with configuration ST2 achieves reductions in the RMS values of azs, zSWS, and FDTL by 5.01%, 15.95%, and 5.43%, respectively, compared with ST0 when the HMDV operates on a Class-C random road profile at a speed of 20 m/s. The findings of this study highlight the potential contribution of ISS to the development of advanced suspension solutions for HMDVs.

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Structural Design and Parameter Optimization of the Inertial Suspension System for Hub Motor Driven Vehicles

  • 会议论文

  • 发表日期：

    2026年

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  • Xiaofeng Yang,
  • Vancuong Bui,
  • Changning Liu,
  • Hong Wang,
  • Tianyi Zhang

摘要

To improve the vibration isolation performance of the hub motor driven vehicles (HMDV) under adverse vibration, this study presents a structural design for a suspension system. Firstly, a quarter HMDV model is developed under the effects of unbalanced radial forces of the switched reluctance motor (SRM) and random road excitation. Based on the analogy between mechanical and electrical networks, two configurations of inertial suspension systems (ISS) are subsequently proposed. The Particle Swarm Optimization (PSO) algorithm is employed to optimize the suspension parameters, aiming to minimize the root mean square (RMS) values of body acceleration (azs), suspension working space (zSWS), and dynamic tyre load (FDTL). Finally, numerical simulations are carried out in the MATLAB/Simulink environment. The results showed that the ISS significantly improves vibration performance compared with the conventional suspension system (ST0). In particular, the ISS with configuration ST2 achieves reductions in the RMS values of azs, zSWS, and FDTL by 5.01%, 15.95%, and 5.43%, respectively, compared with ST0 when the HMDV operates on a Class-C random road profile at a speed of 20 m/s. The findings of this study highlight the potential contribution of ISS to the development of advanced suspension solutions for HMDVs.