Real-Time Energy-Efficient Control for Fully Electric Vehicles Based on an Explicit Model Predictive Control Method

With zero emissions and high energy efficiency, the fully electric vehicle (FEV) is universally becoming more popular. However, limited driving range is one of the primary weaknesses of FEVs. Recently, with the rapid development of intelligent transportation systems, various types of traffic information are available to the vehicle control system, and energy-efficient control of FEVs can be realized based on this information to further extend the total driving range. In this paper, the movement of a preceding vehicle is predicted within each control horizon with vehicle-to-vehicle wireless communication technology, and a better understanding of the future movement of preceding vehicles is established. An explicit model predictive control (EMPC) method is developed to realize real-time control, with the objective of reducing driving energy consumption while maintaining a suitable distance between the preceding vehicles. Dynamic driving simulator is utilized to collect driving data and showcase the effectiveness of the EMPC method. Simulation results show that the proposed real-time control method improves driving energy efficiency in most scenarios and better energy saving results can be observed.