Hybrid Energy Management of Solid Oxide Fuel Cell/Lithium Battery System
Regular Papers|更新时间:2026-02-06
|
Hybrid Energy Management of Solid Oxide Fuel Cell/Lithium Battery System
Hybrid Energy Management of Solid Oxide Fuel Cell/Lithium Battery System
中国电机工程学会电力与能源系统学报(英文)2025年11卷第4期 页码:1610-1624
作者机构:
1. Key Laboratory of Image Processing and Intelligent Control of Education Ministry, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology,Wuhan,China
2. Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, College of Computer Science and Technology, Wuhan University of Science and Technology,Wuhan,China
Dong Li, Xiaobo Zhong, Yuanwu Xu, 等. Hybrid Energy Management of Solid Oxide Fuel Cell/Lithium Battery System[J]. 中国电机工程学会电力与能源系统学报(英文), 2025,11(4):1610-1624.
Dong Li, Xiaobo Zhong, Yuanwu Xu, et al. Hybrid Energy Management of Solid Oxide Fuel Cell/Lithium Battery System[J]. CSEE Journal of Power and Energy Systems, 2025, 11(4): 1610-1624.
Dong Li, Xiaobo Zhong, Yuanwu Xu, et al. Hybrid Energy Management of Solid Oxide Fuel Cell/Lithium Battery System[J]. CSEE Journal of Power and Energy Systems, 2025, 11(4): 1610-1624. DOI: 10.17775/CSEEJPES.2021.00640.
Hybrid Energy Management of Solid Oxide Fuel Cell/Lithium Battery System
摘要
Abstract
The research of the fuel cell and lithium battery hybrid system has attracted more and more researchers because of its advantages of low emission. However
the lower efficiency of energy management has been a critical factor that obstructs the commercialization of the hybrid system. In this study
based on finite element ideas
a solid oxide full cell node model is developed to accurately estimate the operating status of the fuel cell. As for the lithium battery
previous energy management studies generally only focused on the state of charge
however
the state of health is also a key parameter for lithium batteries. In this paper
considering the strong coupling between variables
we use a particle filter algorithm to jointly estimate the state of charge and state of health. To reasonably distribute and manage the energy in the hybrid system
a T-S fuzzy controller for the hybrid system is designed by controlling the state variables in the SOFC model and the state of lithium battery. Finally
our algorithm is verified by using the DSPACE simulation platform. The results show that the hybrid system with an energy management strategy not only meets the real-time sharply changing demands
but also ensures the hybrid system is working efficiently and safely.