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Energy Management Strategy for Dual-Motor Two-Speed Transmission Electric Vehicles Based on Dynamic Programming Algorithm Optimization
Abstract:
In this article, an integrated “dual-motor automated mechanical transmission” configuration was proposed for battery electric vehicles, and a rule-based energy management strategy based on dynamic programming (DP) algorithm optimization was designed. The rule-based energy management strategy was used for online control, and the DP algorithm was used to optimize the control parameters of the rule-based energy management strategy offline. Finally, the optimization results were validated online using the hardware-in-the-loop simulation platform. The results showed that on average, the optimized rule-based energy management strategy can reduce energy consumption by 4.16% under the New European Driving Cycle, Urban Dynamometer Driving Schedule, and Japan 1015 cycle conditions. More importantly, there were evident energy-saving effects on the United States 06, China Light-Duty Vehicle Test Cycle-Passenger, and Highway Fuel Economy Test cycle conditions, which did not participate in the optimization of the rule-based energy management strategy by the DP algorithm.