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Energy Management Strategy Based on Optimal System Operation Loss for a Fuel Cell Hybrid Electric Vehicle

Authors :
Wang, Tianhong
Qiu, Yibin
Xie, Shuqi
Li, Qi
Chen, Weirong
Breaz, Elena
Ravey, Alexandre
Gao, Fei
Source :
IEEE Transactions on Industrial Electronics; 2024, Vol. 71 Issue: 3 p2650-2661, 12p
Publication Year :
2024

Abstract

High operating cost and deficient longevity of stacks are the two primary factors that hinder the widespread commercial usage of fuel cell (FC) technology. In addition, most existing strategies concentrate solely on ameliorating system operating efficiency or fuel consumption, without fully considering the impact of other factors, such as the degradation of power source performance. Thereby, based on the above research background, in this article, we present an energy management strategy based on optimal system operation loss, which considers various parameters, such as power sources’ durability, to minimize the operating cost of electric vehicles. To accomplish this objective, this study formulates a life-cycle operating loss evaluation function related to the lifetime loss of the power sources and the hydrogen consumption cost of the FC. Additionally, the voltage loss is also utilized to evaluate the operating performance of the FC to restrict its output power fluctuation rate. In addition, this study also considers limiting the variation of the battery's state of charge in order to decrease the equivalent hydrogen consumption of the system. Moreover, the high-efficiency operation zone for the stack is also divided. Additionally, given that the performance of FC is related to the working condition, an extended Kalman filter algorithm is used to update the operation parameters of the FC in real time. The experimental results show that the proposed strategy has approximate global optimization ability and compared with equivalent hydrogen consumption minimization strategy and state machine control strategy, it can reduce the operating cost by 19.69% and 28.18%, respectively.

Details

Language :
English
ISSN :
02780046 and 15579948
Volume :
71
Issue :
3
Database :
Supplemental Index
Journal :
IEEE Transactions on Industrial Electronics
Publication Type :
Periodical
Accession number :
ejs64088373
Full Text :
https://doi.org/10.1109/TIE.2023.3269477