Energy-Optimal Adaptive Cruise Control for Electric Vehicles in Both Time and Space Domain based on Model Predictive Control

Abstract

Abstract A novel energy-optimal adaptive cruise control (EACC) function based on model predictive control (MPC) is developed for electric vehicles (EV). Through exploiting the surrounding traffic information, MPC based EACC plans an optimal speed trajectory for the controlled host car, in order to reduce its energy consumption and track its preceding car at the same time. As applying MPC to control an EV faces the challenges of optimizing a non-convex cost function and dealing with non-linear system dynamics, this work proposes more appropriate MPC problem formulations in both time and space domain. The performance of four different MPC designs is compared in a test cycle, which meets the trip requirements of a real driving emissions (RDE) test, according to the European regulation (European Commission, 2016).