Slope-weighted Energy-based Rapid Control Analysis for Hybrid Electric Vehicles

Recent studies have addressed the development of optimal control strategies for hybrid electric vehicles (HEVs). Achieving global optimality for the fuel economy prediction while minimizing the computational efficiency still is a research and development challenge. This paper aims at presenting a novel technique for managing the energy flows in a power split HEV named slope-weighted energy-based rapid control analysis (SERCA). After presenting the HEV plant model and the optimal control problem, the currently most adopted energy management strategies are analyzed. The SERCA technique is then illustrated and its operating steps are detailed. The simulation results for the considered HEV energy management strategies in the standard urban driving cycle subsequently indicate that the SERCA can efficiently achieve near-optimal fuel economy while limiting the computational costs. This suggests the potential use of SERCA for rapid component sizing of HEV powertrains.