Hybrid Model Predictive Control of Semiactive Suspension in Electric Vehicle with Hub-Motor

In hub-motor electric vehicles (HM-EVs), the unbalanced electromagnetic force generated by the HM will further deteriorate the dynamic performance of the electric vehicle. In this paper, a semiactive suspension control method is proposed for HM-EVs. A quarter HM-EV model with an electromechanical coupling effect is established.The model consists of three parts: a motor model, road excitation model and vehicle model. A hybrid model predictive controller (HMPC) is designed based on the developed model, taking into account the nonlinear constraints of damping force. The focus is on improving the vertical performance of the HM-EV. Then, a Kalman filter is designed to provide the required state variables for the controller. The proposed control algorithm and constrained optimal control (COC) algorithm are simulation compared under random road excitation and bump road excitation, and the results show that the proposed control algorithm can improve ride comfort, reduce motor vibration, and improve handling stability more substantially.

Automated summary

A semiactive suspension control method is proposed for hub-motor electric vehicles, with a hybrid model predictive controller (HMPC) designed to improve vehicle dynamic performance. A Kalman filter is used to provide state variables for the controller, and simulation results show that the proposed control algorithm can significantly improve ride comfort, reduce motor vibration, and enhance handling stability.