Multi-Mode Switching Control Strategy for IWM-EV Active Energy-Regenerative Suspension Based on Pavement Level Recognition

Abstract

Aiming at the problems of poor overall vibration reduction and high energy consumption of in-wheel motor-driven electric vehicle (IWM-EV) active suspension on mixed pavement, a multi-mode switching control strategy based on pavement identification and particle swarm optimization is proposed. First, the whole vehicle dynamic model containing active energy-regenerative suspension and the reference model was established, and the sliding mode controller and PID controller designed, respectively, to suppress the vertical vibration of the vehicle and the in-wheel motor. Second, a road grade recognition model based on the dynamic travel signal of the suspension and the road grade coefficient was established to identify the road grade, and then the dynamic performance and energy-feedback characteristics of suspension were optimized by particle swarm optimization. According to the results of pavement identification, the optimal solution of the suspension controller parameters under each working mode was divided and selected to realize the switch of the suspension working mode. The simulation results show that the control strategy can accurately identify the grade of road surface under the condition of mixed road surface, and the ride index of the optimized active energy-regenerative suspension is obviously improved, while some energy is recovered.