Velocity Optimization for Braking Energy Management of In-Wheel Motor Electric Vehicles

This paper presents two braking regenerative energy optimization controllers for in-wheel motor electric vehicles. The first one is a velocity-tracking controller based on a model predictive control (MPC) method to recover the braking energy. It takes the front and rears in-wheel motor efficiencies into account to distribute the hydraulic and in-wheel motor braking torque of the front and rear wheels. As the vehicle information and intelligence have brought new opportunities for energy management, another velocity optimization controller is designed by considering the restricted condition of terminal distance and terminal velocity. In this strategy, a receding-horizon MPC method is proposed to solve the restricted nonlinear optimal problem. Furthermore, this optimization algorithm is transformed from the time horizon to the distance horizon to satisfy the terminal distance constraint. AMESim/Simulink co-simulations are carried out to evaluate the effectiveness of the proposed controllers. The simulation results indicate that the velocity optimization method can achieve the braking requirement as well as effectively promote regenerative efficiency.