Integrated Vibration Control of In-Wheel Motor-Suspensions Coupling System via Dynamics Parameter Optimization

Abstract

In order to integrally control the vibration of in-wheel motor- (IWM-) suspensions coupling system of an electric vehicle, a novel nonlinear dynamics model of the coupling system, which consists of the motor magnetic gap (MMG), is established. Synthesizing subtargets of the vertical vibration acceleration of bodywork, the vertical deformation of tire, the suspension travel, and the vertical fluctuation of MMG, a composite optimization mathematical model is set up. Based on artificial fish swarm algorithm (AFSA), a novel dynamics parameter optimization method is proposed to search the optimal parameter combination existing in the nonlinear dynamics model. Simulation analyses demonstrate that the proposed optimization method is superior to genetic algorithm (GA) under the same optimization conditions, and it can significantly decrease the fluctuation of MMG and improve ride comfort.