This study develops a full-vehicle dynamic model (FVDM) of an electric vehicle (EV) equipped with a front MacPherson independent suspension and a rear torsion-beam suspension to investigate the effects of suspension parameters on ride comfort. Numerical simulations are conducted in MATLAB/Simulink using four weighted-RMS acceleration metrics defined by ISO 2631-1:1997, under ISO class-B road excitation at 80 km/h and full load. Results show that increasing suspension stiffness ki deteriorates ride comfort, whereas higher damping coefficients ci effectively suppress vertical and angular accelerations, thereby enhancing EV ride comfort. An optimal parameter region of 0.6 ≤ ki/k0 ≤ 0.9 and 1.0 ≤ ci/c0 ≤ 1.4 is identified for highway conditions. These findings provide a theoretical basis for the optimal design and potential control strategies of suspension systems in next-generation electric vehicles.

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Numerical Evaluation of Suspension Parameter Effects on Ride Comfort of Electric Vehicles

  • The Minh Huong,
  • Dang Quang Tuyen,
  • Nguyen Tien Duy,
  • Tran The Tran,
  • Le Van Quynh

摘要

This study develops a full-vehicle dynamic model (FVDM) of an electric vehicle (EV) equipped with a front MacPherson independent suspension and a rear torsion-beam suspension to investigate the effects of suspension parameters on ride comfort. Numerical simulations are conducted in MATLAB/Simulink using four weighted-RMS acceleration metrics defined by ISO 2631-1:1997, under ISO class-B road excitation at 80 km/h and full load. Results show that increasing suspension stiffness ki deteriorates ride comfort, whereas higher damping coefficients ci effectively suppress vertical and angular accelerations, thereby enhancing EV ride comfort. An optimal parameter region of 0.6 ≤ ki/k0 ≤ 0.9 and 1.0 ≤ ci/c0 ≤ 1.4 is identified for highway conditions. These findings provide a theoretical basis for the optimal design and potential control strategies of suspension systems in next-generation electric vehicles.