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Modeling Analysis of SOFC System Oriented to Working Condition Identification

Author

Listed:
  • Xiao-Long Wu

    (School of Information Engineering, Nanchang University, Nanchang 330031, China
    Shenzhen Research Institute, Huazhong University of Science and Technology, Shenzhen 518063, China)

  • Hong Zhang

    (School of Information Engineering, Nanchang University, Nanchang 330031, China
    School of Mathematics and Computer Sciences, Nanchang University, Nanchang 330031, China)

  • Hongli Liu

    (School of Information Engineering, Nanchang University, Nanchang 330031, China)

  • Yuan-Wu Xu

    (School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)

  • Jingxuan Peng

    (School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Zhiping Xia

    (School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yongan Wang

    (State Grid Hubei Maintenance Company, Wuhan 430050, China)

Abstract

Solid oxide fuel cell (SOFC) generation system is an important equipment to realize “carbon neutralization”. In SOFC system, a fault will cause changes in working conditions, which is difficult to detect early and find the reason due to the high temperature and seal environment. Therefore, the mechanistic model is a feasible way to find the reasons for the change of system working conditions. In this paper, based on the first law of thermodynamics, the system model of SOFC is built under multiple working conditions, and the influence of stack, afterburner, heat exchanger, and reformer fault is studied on the thermoelectric characteristics and efficiency of the system. The results show that with the introduction of these fault mechanistic models, the dynamic response characteristics of SOFC system under multiple working conditions can be obtained by tracking the key performance parameters qualitatively. The work of this paper is helpful for the guidance of the fault diagnosis of SOFC system in the future.

Suggested Citation

  • Xiao-Long Wu & Hong Zhang & Hongli Liu & Yuan-Wu Xu & Jingxuan Peng & Zhiping Xia & Yongan Wang, 2022. "Modeling Analysis of SOFC System Oriented to Working Condition Identification," Energies, MDPI, vol. 15(5), pages 1-19, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1804-:d:761193
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    References listed on IDEAS

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