Health degradation assessment of proton exchange membrane fuel cell based on an analytical equivalent circuit model. (15th September 2020)

• Record Type: Journal Article
• Authors: Pan, Rui; Yang, Duo; Wang, Yujie; Chen, Zonghai
• Is Part Of: Energy. Volume 207(2020)
• Publication Date: 2020-09-15
• Subjects: Proton exchange membrane fuel cell -- State of health -- Analytical equivalent circuit model -- Electrochemical impedance spectroscopy; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.118185
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The durability of proton exchange membrane fuel cell is worse than the traditional power generation system, which restricts its commercial applications. Accurate state of health of fuel cell plays an important role in ensuring its long-life operation and minimizing maintenance costs. This paper focuses on health forecasting based on electrochemical impedance and analytical equivalent circuit model. The proposed model matches the Nyquist diagram by electrode dynamics analysis, and then the complex nonlinear least square method is used to identify the model parameters. In order to describe the degradation accurately, the parameters with significant aging properties are selected to estimate the state of health based on linear regression. Then, the estimated impedance of four characteristic frequency points, which can represent the overall outline of the impedance spectrum, is used to evaluate the accuracy of the proposed method. The effectiveness of aging datasets are verified by Kramers-Kronig transformation, and the predictive capability of the proposed method are demonstrated by two aging datasets. Compared with other method, the experimental results show the superiority of the proposed method, which can provide accurate health forecasting and help to improve performance of the voltage degradation prediction. Highlights: The two aging tests are used to assess the health degradation of fuel cell. The Kramers-Kronig transformation is used to validate the data effectiveness. An analytical equivalent circuit model is used to fit the impedance spectroscopy. The complex nonlinear least square method is used for parameters identification. The impedance is introduced to characterize the voltage recovery phenomenon.