Simulation analysis and optimization of ride quality of in-wheel motor electric vehicle

• Main Authors: Zheng Yang, Chen Yong, Zhao Li, Yin Kangsheng
• Format: Article
• Language: English
• Published: SAGE Publishing 2018-05-01
• Series: Advances in Mechanical Engineering
• Online Access: https://doi.org/10.1177/1687814018776543

In order to evaluate the influence of unsprung mass on ride comfort for an in-wheel motor electric vehicle, an improved genetic algorithm based on fitness evaluation was proposed to optimize the suspension system. The simulation model was established in ADAMS software for the target sports utility vehicle with front McPherson and rear unequal length double arm suspension systems. The ride comfort of the target vehicle was analyzed by the developed simulation model. The stiffness and damping of the suspensions were optimized by the root mean square values of the vehicle weighted vertical acceleration and the pitching angle acceleration with the help of the multi-disciplinary and multi-objective optimization software, ISIGHT. The results show that, the proposed multi-objective optimization algorithm is helpful to achieve the ride comfort improvement and the computation time reduction.