Performance of an Eco-Driving Nonlinear MPC System for a Power-Split HEV during Car Following

Abstract

In this paper, the authors presents an eco-driving nonlinear model predictive control (MPC) approach for the energy management problem of a power-split hybrid electric vehicle (HEV) system during car following. This paper adds four new contributions to this field. First, the proposed method optimizes fuel economy under the HEV physical constraints that include the upper bounds of the speed and torque of engines, motors and generators and the battery state of charge at each time. Second, in the proposed method the performance index is designed in a systematic way, which can be easily understood by designers. Third, the proposed method gives the freedom of vehicle spacing between the preceding vehicle and the host one. Fourth, using the HEV property, the desired battery state of charge is designed according to the road slopes for better recuperation of free braking energy. Computer simulation results showed that the fuel economy was much better using the nonlinear model predictive control approach than using the ADVISOR rule-based approach. The authors conclude that the nonlinear model predictive control approach is effective for the energy management problem of the power-split hybrid electric vehicle system during car following.