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Coupling electrochemical impedance spectroscopy and model-based aging estimation for solid oxide fuel cell stacks lifetime prediction

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  • Gallo, Marco
  • Polverino, Pierpaolo
  • Mougin, Julie
  • Morel, Bertrand
  • Pianese, Cesare

Abstract

In this work, an online natural aging estimation algorithm is developed, coupled with an Electrochemical Impedance Spectroscopy (EIS)-based diagnostic algorithm, to refine detection features extraction during Solid Oxide Fuel Cell (SOFC) stack operation and to predict its Remaining Useful Life (RUL). A combination of a lumped dynamic model along with features extracted from real-time EIS measurements is herein proposed for on-line applications. An Equivalent Circuit Model (ECM) is considered to identify parameters, such as ohmic and total resistance, that are coupled with an Area Specific Resistance (ASR) approach within the lumped model. The information derived from the EIS spectrum allows to estimate the voltage degradation over time along with its nominal behaviour. Indeed, the time trend of the identified parameters is proportional to the aging of the cell if no other abnormal condition occurs. This guarantees an on-line RUL estimation and a more robust diagnostic algorithm for fault detection and isolation. The approach has been applied to a 6-cells anode supported short stack tested for about 5000 h, and the related RUL estimation identified a critical issue on the middle cell, affecting its neighbours.

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  • Gallo, Marco & Polverino, Pierpaolo & Mougin, Julie & Morel, Bertrand & Pianese, Cesare, 2020. "Coupling electrochemical impedance spectroscopy and model-based aging estimation for solid oxide fuel cell stacks lifetime prediction," Applied Energy, Elsevier, vol. 279(C).
    • Handle: RePEc:eee:appene:v:279:y:2020:i:c:s0306261920312113
    DOI: 10.1016/j.apenergy.2020.115718
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    References listed on IDEAS

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    1. Polverino, Pierpaolo & Sorrentino, Marco & Pianese, Cesare, 2017. "A model-based diagnostic technique to enhance faults isolability in Solid Oxide Fuel Cell systems," Applied Energy, Elsevier, vol. 204(C), pages 1198-1214.
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    4. Wu, Xiao-long & Xu, Yuan-Wu & Xue, Tao & Zhao, Dong-qi & Jiang, Jianhua & Deng, Zhonghua & Fu, Xiaowei & Li, Xi, 2019. "Health state prediction and analysis of SOFC system based on the data-driven entire stage experiment," Applied Energy, Elsevier, vol. 248(C), pages 126-140.
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    2. Zeyu Lin & Hamdi Ayed & Belgacem Bouallegue & Hana Tomaskova & Saeid Jafarzadeh Ghoushchi & Gholamreza Haseli, 2021. "An Integrated Mathematical Attitude Utilizing Fully Fuzzy BWM and Fuzzy WASPAS for Risk Evaluation in a SOFC," Mathematics, MDPI, vol. 9(18), pages 1-18, September.
    3. Zhao, Lei & Hong, Jichao & Xie, Jiaping & Jiang, Shangfeng & Wei, Xuezhe & Ming, Pingwen & Dai, Haifeng, 2023. "Investigation of local sensitivity for vehicle-oriented fuel cell stacks based on electrochemical impedance spectroscopy," Energy, Elsevier, vol. 262(PA).
    4. Yuanwu Xu & Hao Shu & Hongchuan Qin & Xiaolong Wu & Jingxuan Peng & Chang Jiang & Zhiping Xia & Yongan Wang & Xi Li, 2022. "Real-Time State of Health Estimation for Solid Oxide Fuel Cells Based on Unscented Kalman Filter," Energies, MDPI, vol. 15(7), pages 1-17, March.
    5. He, Wenbin & Liu, Ting & Ming, Wuyi & Li, Zongze & Du, Jinguang & Li, Xiaoke & Guo, Xudong & Sun, Peiyan, 2024. "Progress in prediction of remaining useful life of hydrogen fuel cells based on deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    6. Mohammad Alboghobeish & Andrea Monforti Ferrario & Davide Pumiglia & Massimiliano Della Pietra & Stephen J. McPhail & Sergii Pylypko & Domenico Borello, 2022. "Developing an Automated Tool for Quantitative Analysis of the Deconvoluted Electrochemical Impedance Response of a Solid Oxide Fuel Cell," Energies, MDPI, vol. 15(10), pages 1-22, May.
    7. Jingxuan Peng & Dongqi Zhao & Yuanwu Xu & Xiaolong Wu & Xi Li, 2023. "Comprehensive Analysis of Solid Oxide Fuel Cell Performance Degradation Mechanism, Prediction, and Optimization Studies," Energies, MDPI, vol. 16(2), pages 1-23, January.
    8. Tiancai Ma & Jiajun Kang & Weikang Lin & Xinru Xu & Yanbo Yang, 2022. "Highly Integrated Online Multi-Channel Electrochemical Impedance Spectroscopy Measurement Device for Fuel Cell Stack," Energies, MDPI, vol. 15(9), pages 1-23, May.
    9. Zhang, Shijie & Tang, Jixia & Chen, Weiyu & Qian, Tu & Li, Xuechen & Feng, Zixuan & He, Jie & Zhang, Rui & Yang, Zhengchun & Li, Huayi & Pan, Peng & Zhang, Kailiang & Zheng, Lingcheng & Feng, Deqiang, 2024. "Advanced flexible photocatalytic fuel cell using TiO2/carbon quantum dots photoanode for green electricity production," Applied Energy, Elsevier, vol. 357(C).
    10. Žnidarič, Luka & Nusev, Gjorgji & Morel, Bertrand & Mougin, Julie & Juričić, Đani & Boškoski, Pavle, 2021. "Evaluating uncertainties in electrochemical impedance spectra of solid oxide fuel cells," Applied Energy, Elsevier, vol. 298(C).

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