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Online implementation of SVM based fault diagnosis strategy for PEMFC systems

Author

Listed:
  • Li, Zhongliang
  • Outbib, Rachid
  • Giurgea, Stefan
  • Hissel, Daniel
  • Jemei, Samir
  • Giraud, Alain
  • Rosini, Sebastien

Abstract

In this paper, the topic of online diagnosis for Polymer Electrolyte Membrane Fuel Cell (PEMFC) systems is addressed. In the diagnosis approach, individual cell voltages are used as the variables for diagnosis. The pattern classification tool Support Vector Machine (SVM) combined with designed diagnosis rule is used to achieve fault detection and isolation (FDI). A highly-compacted embedded system of the System in Package (SiP) type is designed and fabricated to monitor individual cell voltages and to perform the diagnosis algorithms. For validation, the diagnosis approach is implemented online on PEMFC experimental platform. Four concerned faults can be detected and isolated in real-time.

Suggested Citation

  • Li, Zhongliang & Outbib, Rachid & Giurgea, Stefan & Hissel, Daniel & Jemei, Samir & Giraud, Alain & Rosini, Sebastien, 2016. "Online implementation of SVM based fault diagnosis strategy for PEMFC systems," Applied Energy, Elsevier, vol. 164(C), pages 284-293.
    • Handle: RePEc:eee:appene:v:164:y:2016:i:c:p:284-293
    DOI: 10.1016/j.apenergy.2015.11.060
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    References listed on IDEAS

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    1. Chen, Huicui & Pei, Pucheng & Song, Mancun, 2015. "Lifetime prediction and the economic lifetime of Proton Exchange Membrane fuel cells," Applied Energy, Elsevier, vol. 142(C), pages 154-163.
    2. Simons, Andrew & Bauer, Christian, 2015. "A life-cycle perspective on automotive fuel cells," Applied Energy, Elsevier, vol. 157(C), pages 884-896.
    3. Kang, Sanggyu & Min, Kyoungdoug, 2016. "Dynamic simulation of a fuel cell hybrid vehicle during the federal test procedure-75 driving cycle," Applied Energy, Elsevier, vol. 161(C), pages 181-196.
    4. Li, Zhongliang & Outbib, Rachid & Giurgea, Stefan & Hissel, Daniel & Li, Yongdong, 2015. "Fault detection and isolation for Polymer Electrolyte Membrane Fuel Cell systems by analyzing cell voltage generated space," Applied Energy, Elsevier, vol. 148(C), pages 260-272.
    5. Cai, Baoping & Liu, Yonghong & Fan, Qian & Zhang, Yunwei & Liu, Zengkai & Yu, Shilin & Ji, Renjie, 2014. "Multi-source information fusion based fault diagnosis of ground-source heat pump using Bayesian network," Applied Energy, Elsevier, vol. 114(C), pages 1-9.
    6. Jang, Jer-Huan & Yan, Wei-Mon & Chiu, Han-Chieh & Lui, Jun-Yi, 2015. "Dynamic cell performance of kW-grade proton exchange membrane fuel cell stack with dead-ended anode," Applied Energy, Elsevier, vol. 142(C), pages 108-114.
    7. Sun, Hong & Xie, Chen & Chen, Hao & Almheiri, Saif, 2015. "A numerical study on the effects of temperature and mass transfer in high temperature PEM fuel cells with ab-PBI membrane," Applied Energy, Elsevier, vol. 160(C), pages 937-944.
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    Cited by:

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    3. Andújar, J.M. & Segura, F. & Isorna, F. & Calderón, A.J., 2018. "Comprehensive diagnosis methodology for faults detection and identification, and performance improvement of Air-Cooled Polymer Electrolyte Fuel Cells," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 193-207.
    4. Oh, Hwanyeong & Lee, Won-Yong & Won, Jinyeon & Kim, Minjin & Choi, Yoon-Young & Han, Soo-Bin, 2020. "Residual-based fault diagnosis for thermal management systems of proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 277(C).
    5. Pedro Andrade & Khaled Laadjal & Adérito Neto Alcaso & Antonio J. Marques Cardoso, 2024. "A Comprehensive Review on Condition Monitoring and Fault Diagnosis in Fuel Cell Systems: Challenges and Issues," Energies, MDPI, vol. 17(3), pages 1-45, January.
    6. Han, Zhezhe & Hossain, Md. Moinul & Wang, Yuwei & Li, Jian & Xu, Chuanlong, 2020. "Combustion stability monitoring through flame imaging and stacked sparse autoencoder based deep neural network," Applied Energy, Elsevier, vol. 259(C).
    7. Young Park, Jin & Seop Lim, In & Ho Lee, Yeong & Lee, Won-Yong & Oh, Hwanyeong & Soo Kim, Min, 2023. "Severity-based fault diagnostic method for polymer electrolyte membrane fuel cell systems," Applied Energy, Elsevier, vol. 332(C).
    8. Zou, Wei & Froning, Dieter & Shi, Yan & Lehnert, Werner, 2020. "A least-squares support vector machine method for modeling transient voltage in polymer electrolyte fuel cells," Applied Energy, Elsevier, vol. 271(C).
    9. Chen, Huicui & Zhao, Xin & Qu, Bingwang & Zhang, Tong & Pei, Pucheng & Li, Congxin, 2018. "An evaluation method of gas distribution quality in dynamic process of proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 232(C), pages 26-35.
    10. Qu, Fuming & Liu, Jinhai & Zhu, Hongfei & Zhou, Bowen, 2020. "Wind turbine fault detection based on expanded linguistic terms and rules using non-singleton fuzzy logic," Applied Energy, Elsevier, vol. 262(C).
    11. Li, Da & Zhang, Zhaosheng & Zhou, Litao & Liu, Peng & Wang, Zhenpo & Deng, Junjun, 2022. "Multi-time-step and multi-parameter prediction for real-world proton exchange membrane fuel cell vehicles (PEMFCVs) toward fault prognosis and energy consumption prediction," Applied Energy, Elsevier, vol. 325(C).
    12. Akimoto, Yutaro & Okajima, Keiichi, 2021. "Simple on-board fault-detection method for proton exchange membrane fuel cell stacks using by semi-empirical curve fitting," Applied Energy, Elsevier, vol. 303(C).
    13. Ajagekar, Akshay & You, Fengqi, 2021. "Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems," Applied Energy, Elsevier, vol. 303(C).
    14. Danqi Su & Jiayang Zheng & Junjie Ma & Zizhe Dong & Zhangjie Chen & Yanzhou Qin, 2023. "Application of Machine Learning in Fuel Cell Research," Energies, MDPI, vol. 16(11), pages 1-32, May.
    15. Behzad Najafi & Paolo Bonomi & Andrea Casalegno & Fabio Rinaldi & Andrea Baricci, 2020. "Rapid Fault Diagnosis of PEM Fuel Cells through Optimal Electrochemical Impedance Spectroscopy Tests," Energies, MDPI, vol. 13(14), pages 1-19, July.
    16. Gao, Q.W. & Liu, W.Y. & Tang, B.P. & Li, G.J., 2018. "A novel wind turbine fault diagnosis method based on intergral extension load mean decomposition multiscale entropy and least squares support vector machine," Renewable Energy, Elsevier, vol. 116(PA), pages 169-175.

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