Control strategy optimization of hybrid electric vehicle for fuel saving based on energy flow experiment and simulation

Abstract

Energy flow analysis is one of the most effective methods for assessing and improving vehicle efficiency. It can provide the most effective support for the development and optimization of a hybrid electric vehicle (HEV) control strategy for improving the performance and energy saving of HEVs. In this study, an energy flow experiment of a series–parallel HEV is conducted in a climate chamber under the Worldwide Light-duty Test Cycle to address high fuel consumption. Then, GT-Suite and MATLAB/Simulink co-simulation models for the tested vehicle are built and calibrated. The problems of the original HEV control strategy are addressed using the analysis of vehicle energy flow distributions, operating conditions, and energy efficiency of key parts. Then, two optimized vehicle control strategies (termed Opt1 and Opt2) are employed to test vehicle fuel savings using a calibrated co-simulation model. The specific optimized vehicle control strategies primarily include canceling the series and parallel charging in the braking state, adding the engine direct-drive mode, and reducing the proportion of the parallel mode. The simulated results show that the 100 km fuel consumptions of Opt1 and Opt2 are reduced by 7.1% and 7.5%, respectively, compared with the original vehicle. The proportion of energy that drives the vehicle directly through the engines of Opt1 and Opt2 is increased from 45.7% to 70.2% and 61.6%, respectively. The total vehicle energy losses for Opt1 and Opt2 decrease from 29.0% to 22.5% and 22.9%, respectively. Although the engine of the original vehicle exhibits high thermal efficiency, the efficiency of the entire powertrain system is the lowest, resulting in the highest fuel consumption.