Energy‐efficiency optimization and control for electric vehicle platooning with regenerating braking

Abstract

Abstract It is a critical problem to improve energy efficiency for electric vehicle platooning systems. Moreover, different from internal combustion engine vehicles, the electric engine has higher efficiency, and further regenerating braking is widely used to recycle part of the energy in the electric vehicle when it is braking. What is more, if vehicles take a formation to drive, they can save more energy. Combining all the favorable factors, this paper presents a two‐layer energy‐efficiency optimization strategy for electric vehicle platooning. The upper layer presents an optimization method to find the optimal velocities and distances between vehicles under different road conditions during the cruise status of the electric vehicle platooning. Due to the nonconvex cost function and considering regenerative braking, the optimization problem is addressed by the dynamic programming method combined with the successive convex approximation method. Further, the lower layer presents a real‐time Model Predictive Control (MPC) strategy, and it directly introduces the battery pack state of charge consumption as the input, which not only finishes the control mission but also consumes minimal energy. Finally, simulation results are provided to verify the effectiveness and advantages of the proposed methods.

Keywords

• autonomous driving
• battery powered vehicles
• control system synthesis
• optimization and uncertainty