Quadratic utility function-based energy management strategy for electric vehicle considering degradation of fuel cells and batteries

The vehicle economy and durability of power sources are strongly affected by the energy management strategy (EMS). In order to balance the economy and durability, this paper proposes a novel EMS based on the quadratic utility function (QUF). Degradation models of fuel cells and batteries are first e...

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Bibliographic Details
Published in:Proceedings of the Institution of Mechanical Engineers. Part D, Journal of automobile engineering Journal of automobile engineering, 2023-03, Vol.237 (4), p.754-765
Main Authors: Sun, Yan, Xia, Changgao, Yin, Bifeng, Han, Jiangyi, Liu, Jing
Format: Article
Language:English
Subjects:
Algorithms
Degradation
Durability
Electric vehicles
Energy management
Finite state machines
Fuel cells
Fuzzy control
Multiple objective analysis
Particle swarm optimization
Power management
Power sources
Utility functions
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Summary:The vehicle economy and durability of power sources are strongly affected by the energy management strategy (EMS). In order to balance the economy and durability, this paper proposes a novel EMS based on the quadratic utility function (QUF). Degradation models of fuel cells and batteries are first established. The QUF and finite state machine (FSM) are then used to decompose the demand current into the output current of fuel cells and batteries. In order to improve the power sources durability and the economy of the vehicle, the actual output characteristics and current change of fuel cells are considered in the QUF, in which the key coefficients are determined and optimized using the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm and the pareto solution set. The simulation results show that the proposed control strategy can efficiently improve the durability of fuel cells and batteries, reduce the hydrogen consumption and extend the driving range. Compared with the FSM control strategy, the proposed strategy can reduce the degradation of the batteries by 19.4%, and extend the driving range by 1.2% under the WLTC driving cycle. Finally, compared with the fuzzy control strategy, the proposed strategy can reduce the degradation of the fuel cells by 52.1%, and extend the driving range by 3.0% under the WLTC driving cycle.
ISSN:0954-4070
2041-2991
DOI:10.1177/09544070221080351