Energy management strategy for long-life fuel cell hybrid power systems based on improved whale optimization algorithm

ABSTRACT

Systems primarily powered by hydrogen fuel cells (FC) have vast application prospects in fields such as automobiles and power generation systems. Extending the useful life of FC systems has been an important goal to promote FC applications. In this paper, a long-life energy management strategy (EMS) is proposed for an FC hybrid power system (FCHPS) consisting of two FCs and one lithium battery (LB). Based on the analysis of FC life degradation characteristics and the dynamic power variations, an FC life degradation model for power optimization is established. Further, a long-life objective with constraints is constructed to optimize the power allocation between two FCs and one LB. To overcome the inefficiency of the traditional whale optimization algorithm (WOA) at the late stage of solving the optimization problem, an improved WOA (IWOA) algorithm based on a linear decay coefficient adjustment is designed to strengthen the search capability. Then, the feasibility and effectiveness of the proposed IWOA are verified in the simulation results. Finally, the experimental results show a 2.26% decrease in life degradation over 24 hours compared with the logic threshold strategy when employing the proposed long-life EMS integrated with IWOA.

GRAPHICAL ABSTRACT

KEYWORDS:

• Fuel cells
• useful life
• energy management strategy
• life degradation
• whale optimization algorithm

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Key Research and Development Program of China under Grant [2022YFB4003800], the National Natural Science Foundation of China under Grants [62273265 and 62173264], and the Fundamental Research Funds for the Central Universities under Grant [WUT:2024IVA041].

Notes on contributors

Zhichao Fu

Zhichao Fu received the Ph.D. degree in Traffic information engineering and control from Wuhan University of Technology, Wuhan, China, in 2024. He is a Senior Engineer with the Wuhan Institute of Marine Electric Propulsion, Wuhan. His research interests include fuel cell control and energy management technology, fuel cell power generation systems, and intelligent algorithm.

Qihong Chen

Qihong Chen received the Ph.D. degree in control science and engineering from Southeast University, Nanjing, China, in 2003. He is currently a Professor with the Wuhan University of Technology, Wuhan, China. His current research interests include grid-tied inverters and predictive control.

Ze Zhou

Ze Zhou received the B.S. degree in automation and the M.S. degree in control science and engineering from Wuhan University of Technology, Wuhan, China, in 2016 and 2019, respectively, and the Ph.D. degree in control science and engineering from Zhejiang University, Hangzhou, China, in 2023. He is currently a Lecturer with the Wuhan University of Technology, Wuhan, China. His research interests include model predictive control, optimization algorithms, and power and transportation systems.

Dongqi Zhao

Dongqi Zhao received the B.S. degree in automation from Chongqing University, Chongqing, China, in 2017, and the Ph.D. degree in control science and engineering from Huazhong University of Science and Technology, Wuhan, China, in 2023. He is currently a postdoc in the Wuhan University of Technology, Wuhan, China. His research interests include control systems, model predictive control, and optimization algorithms.

Shuiying Yu

Shuiying Yu received the Ph.D. in computer system structure from Huazhong University of Science and Technology, Wuhan, China, in 2023. She is currently an associate professor with Wuhan Institute of Shipbuilding Technology. Her research interests include computer systems, distributed systems, big data processing, and smart energy.

Liyan Zhang

Liyan Zhang received the Ph.D. degree in control science and engineering from Zhejiang University, Hangzhou, China, in 2004. He is currently a Professor with the Wuhan University of Technology, Wuhan, China. His research interests include wireless power transfer and control of hybrid electric vehicles.