Real-Time State of Health Estimation for Solid Oxide Fuel Cells Based on Unscented Kalman Filter

Yuanwu Xu, Hao Shu, Hongchuan Qin, Xiaolong Wu, Jingxuan Peng, Chang Jiang, Zhiping Xia, Yongan Wang and Xi Li
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Yuanwu Xu: School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
Hao Shu: School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
Hongchuan Qin: Key Laboratory of Image Processing and Intelligent Control of Education Ministry, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Xiaolong Wu: School of Information Engineering, Nanchang University, Nanchang 330031, China
Jingxuan Peng: Key Laboratory of Image Processing and Intelligent Control of Education Ministry, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Chang Jiang: Key Laboratory of Image Processing and Intelligent Control of Education Ministry, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Zhiping Xia: Key Laboratory of Image Processing and Intelligent Control of Education Ministry, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Yongan Wang: State Grid Hubei Maintenance Company, Wuhan 430077, China
Xi Li: Key Laboratory of Image Processing and Intelligent Control of Education Ministry, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China

Energies, 2022, vol. 15, issue 7, 1-17

Abstract: The evolution of performance degradation has become a major obstacle to the long-life operation of the Solid Oxide Fuel Cell (SOFC) system. The feasibility of employing degradation resistance to assess the State of Health (SOH) is proposed and verified. In addition, a real-time Unscented Kalman Filter (UKF) based SOH estimation method is further proposed to eliminate the disturbance of calculating the SOH directly utilizing measurement and electric balance model. The results of real-time SOH estimation with an UKF under constant and varying load conditions demonstrate the feasibility and effectiveness of the SOFC performance degradation assessment method.

Keywords: Solid Oxide Fuel Cell; state of health estimation; degradation resistance; Unscented Kalman Filter (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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