Adaptive energy management strategy for hybrid batteries/supercapacitors electrical vehicle based on model prediction control

• Published in: Asian journal of control Vol. 22; no. 6; pp. 2476 - 2486
• Main Authors: Fu, Zhumu, Li, Zhenhui, Tao, Fazhan
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 01.11.2020
• Subjects: Adaptive control; adaptive method; Control methods; Energy management; energy management strategy; hybrid electrical vehicle; Hybrid vehicles; Life span; model prediction control; Strategy; Supercapacitors; Vehicles
• ISSN: 1561-8625; 1934-6093
• DOI: 10.1002/asjc.2180

In this paper, in order to extend battery lifespan and lift power performance in hybrid batteries/supercapacitors electrical vehicles, a new energy management strategy is proposed based on model prediction control and adaptive method. Firstly, models of batteries and supercapacitors are built, which are then adapted and simplified to develop state space expression. Secondly, a series of reference values of battery power and supercapacitor state of charge for model prediction methods are properly calculated by the adaptive method. Thereafter, an energy management strategy based on the model prediction control method is designed to allocate the output power of batteries and supercapacitors within constraints, which guarantees batteries lifespan and the power performance of vehicle. Finally, simulation and experiment results are provided to evaluate battery lifespan and power performance of vehicles under HWFET and UDDS road conditions. The results obtained show that the proposed strategy, compared with the former methods, reduce average power and power variation of batteries, and effectively utilize supercapacitors depending on the power demand, which can extend battery lifespan and lift the power performance of vehicle.