Energy Management Strategy for Dual-Motor Two-Speed Transmission Electric Vehicles Based on Dynamic Programming Algorithm Optimization 14-10-01-0002
This also appears in
SAE International Journal of Electrified Vehicles-V130-14EJ
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.
Citation: Wu, B. and Zhang, S., "Energy Management Strategy for Dual-Motor Two-Speed Transmission Electric Vehicles Based on Dynamic Programming Algorithm Optimization," SAE Int. J. Elec. Veh. 10(1):19-31, 2021, https://doi.org/10.4271/14-10-01-0002. Download Citation
Author(s):
Bin Wu, Suxu Zhang
Affiliated:
Beijing University of Technology, China
Pages: 14
ISSN:
2691-3747
e-ISSN:
2691-3755
Related Topics:
Electric vehicles
Fuel economy
Optimization
Simulation and modeling
Energy consumption
Mathematical models
Hardware-in-the-loop
Internet
Transmissions
SAE MOBILUS
Subscribers can view annotate, and download all of SAE's content.
Learn More »