Design and optimization of equivalent consumption minimization strategy for 4WD hybrid electric vehicles incorporating vehicle connectivity

Abstract

This paper presents an optimized equivalent consumption minimization strategy (ECMS) for four-wheel-drive (4WD) hybrid electric vehicles (HEVs) incorporating vehicle connectivity. In order to be applicable to the 4WD architecture, the ECMS is designed based on a rule-based strategy and used under the condition that a certain propulsion mode is activated. Assuming that a group of 4WD HEVs are connected and position information can be shared with each other, we formulate a decentralized model predictive control (MPC) framework that compromises fuel efficiency, mobility, and inter-vehicle distance to optimize the velocity profile of each individual vehicle. Based on the optimized velocity profile, an optimization problem considering both fuel economy and battery state of charge (SOC) sustainability is formulated to optimize the equivalent factors (EFs) of the ECMS for HEVs over an appropriate time window. MATLAB User Datagram Protocol (UDP) is used in the codes run on multiple computers to simulate the wireless communication among vehicles, which share position information via UDP-based communication, and dSPACE is used as a software-in-the-loop platform for the simulation of the optimized ECMS. Simulation results validate the control effectiveness of the proposed method.