Correlation between Braking Strategy and Regenerative Braking Energy of Electric Vehicle

This paper proposes a model predictive control (MPC) strategy for braking velocity optimization problem in distance domain of electric vehicle (EV). Firstly, the longitudinal dynamic model and energy consumption model are built, in which the energy loss including motor generation loss, driving resistance loss and mechanical braking loss are discussed in detail. Then based on model predictive control, the braking control strategy is transforming into the optimization problem for driving economy, safety and speed tracking under multiple constraints, such as motor speed, torque and battery power generation for different state of charge (SOC). The particle swarm optimization (PSO) algorithm is introduced to deal with the nonlinear model predictive control (NMPC) problem. Finally, numerical simulations show that the braking strategy proposed can improve the recovery energy rate by 4.82% under normal battery SOC and 9.9% under high battery SOC, which limits the power generation of motor.