Energy-Optimal Adaptive Cruise Control for Electric Vehicles Based on Model Predictive Control and Dynamic Programming

Eco-driving as a control method to improve vehicle energy-saving performance has attracted considerable attention. In order to avoid the disadvantages of a single control method, this paper integrates the model predictive control (MPC) algorithm and dynamic programming (DP) strategy and proposes a fast and efficient energy-optimal adaptive cruise control (EACC), which satisfies the following performance of vehicles at multi-signal intersections. In this study, the vehicle system dynamics model and the vehicle controller are first built. Then, MATLAB/Simulink was used for simulation verification. The results of vehicle energy performance and following performance are obtained through simulation experiments under two different working conditions of the road and the front vehicle, and the simulation results verify the effectiveness of the proposed method.