Comparison of Rule-Based and Optimization-Based Energy Management Strategies for Hybrid Electric Vehicles
Abstract
The energy management method adopted by hybrid electric vehicles is the core technology of vehicle fuel economy. At present, there is still a lack of systematic and quantitative comparative analysis on the main strategies. In this paper, the power split hybrid electric vehicle is taken as the research object, and a complete simulation scheme is proposed: the engine fuel consumption map, motor efficiency map, step internal resistance battery, and vehicle longitudinal power are included. Based on this, three typical energy management ideas are compared, and the driving cycles shown in Urban Dynamometer Driving Schedule (UDDS), Highway Fuel Economy Test (HWFET), and Worldwide Harmonized Light-Duty Vehicles Test Cycle (WLTC) are used for the test, and a comprehensive judgment is made according to the equivalent fuel consumption per 100 kilometers, State of Charge (SOC) retention capacity, operation efficiency, and condition matching degree. From the existing literature, it can be concluded that dynamic programming gives the theoretical minimum fuel consumption in each working condition, which is the reference standard of performance limit; The fuel consumption difference between the adaptive equivalent fuel consumption minimization method and the dynamic programming method is about 5% at most, and it allows online real-time use, which is an ideal practical coexistence scheme; Although the strategy designed according to the rules can handle the working conditions under calibration, the fuel consumption under non-standard working conditions often increases by more than 10%, and the adaptability is not strong.