LAPSE:2023.14289v1
Published Article
LAPSE:2023.14289v1
Real-Time State of Health Estimation for Solid Oxide Fuel Cells Based on Unscented Kalman Filter
March 1, 2023
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.
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.
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Keywords
degradation resistance, Solid Oxide Fuel Cell, state of health estimation, Unscented Kalman Filter
Subject
Suggested Citation
Xu Y, Shu H, Qin H, Wu X, Peng J, Jiang C, Xia Z, Wang Y, Li X. Real-Time State of Health Estimation for Solid Oxide Fuel Cells Based on Unscented Kalman Filter. (2023). LAPSE:2023.14289v1
Author Affiliations
Xu Y: School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
Shu H: School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
Qin H: 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
Wu X: School of Information Engineering, Nanchang University, Nanchang 330031, China; Shenzhen Research Institute, Huazhong University of Science and Technology, Shenzhen 518063, China
Peng J: 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 [ORCID]
Jiang C: 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
Xia Z: 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
Wang Y: State Grid Hubei Maintenance Company, Wuhan 430077, China [ORCID]
Li X: 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; Shenzhen Research Institute, Huazhong University of Sci
Shu H: School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
Qin H: 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
Wu X: School of Information Engineering, Nanchang University, Nanchang 330031, China; Shenzhen Research Institute, Huazhong University of Science and Technology, Shenzhen 518063, China
Peng J: 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 [ORCID]
Jiang C: 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
Xia Z: 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
Wang Y: State Grid Hubei Maintenance Company, Wuhan 430077, China [ORCID]
Li X: 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; Shenzhen Research Institute, Huazhong University of Sci
Journal Name
Energies
Volume
15
Issue
7
First Page
2534
Year
2022
Publication Date
2022-03-30
ISSN
1996-1073
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PII: en15072534, Publication Type: Journal Article
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LAPSE:2023.14289v1
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https://doi.org/10.3390/en15072534
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Mar 1, 2023
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