Hierarchical energy management control strategies for connected hybrid electric vehicles considering efficiencies feedback

Abstract

This paper presents a closed-loop hierarchical energy management control strategy for a group of connected hybrid electric vehicles (HEVs) considering the feedback of propulsion and recuperation efficiencies. The higher level controller utilizes model predictive control (MPC) incorporating signal phase and timing (SPAT) information for the prediction of the optimal velocity profile over a finite time horizon, with periodically updated efficiencies from the lower level controller. The adaptive equivalent consumption minimization strategy (A-ECMS)-based lower level controller then makes use of the optimal velocity profile for the energy management control of the HEVs. Meanwhile, the lower level controller calculates and feeds back the average propulsion and recuperation efficiencies of the current time window to the higher level controller, which updates the efficiencies with the average values and corrects the fuel consumption model for the calculation of the velocity profile of the next time window. Simulation results validate the control effectiveness of the proposed control strategy.