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A signal-based method for fast PEMFC diagnosis

Author

Listed:
  • Pahon, E.
  • Yousfi Steiner, N.
  • Jemei, S.
  • Hissel, D.
  • Moçoteguy, P.

Abstract

This paper deals with a novel signal-based method for fault diagnosis of a proton exchange membrane fuel cell (PEMFC). Thanks to an in-lab test bench used for the experimental tests, various parameters can be recorded as electrical or fluidic measurements. The chosen input signal for the diagnosis uses no additional expensive and no intrusive sensors specifically dedicated for the diagnosis task. It uses insofar only the already existing sensors on the system. This paper focuses on the detection and identification of a high air stoichiometry (HAS) fault. The wavelet transform (WT) and more precisely the energy contained in each detail of the wavelet decomposition is used to diagnose quickly an oversupply of air to the fuel cell system. Finally, some experimental results are presented according to different input signals, in order to prove the efficiency of the patented method.

Suggested Citation

  • Pahon, E. & Yousfi Steiner, N. & Jemei, S. & Hissel, D. & Moçoteguy, P., 2016. "A signal-based method for fast PEMFC diagnosis," Applied Energy, Elsevier, vol. 165(C), pages 748-758.
    • Handle: RePEc:eee:appene:v:165:y:2016:i:c:p:748-758
    DOI: 10.1016/j.apenergy.2015.12.084
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    References listed on IDEAS

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    1. Pei, Pucheng & Chen, Huicui, 2014. "Main factors affecting the lifetime of Proton Exchange Membrane fuel cells in vehicle applications: A review," Applied Energy, Elsevier, vol. 125(C), pages 60-75.
    2. Bonvini, Marco & Sohn, Michael D. & Granderson, Jessica & Wetter, Michael & Piette, Mary Ann, 2014. "Robust on-line fault detection diagnosis for HVAC components based on nonlinear state estimation techniques," Applied Energy, Elsevier, vol. 124(C), pages 156-166.
    3. Yan, Wei-Mon & Wang, Xiao-Dong & Lee, Duu-Jong & Zhang, Xin-Xin & Guo, Yi-Fan & Su, Ay, 2011. "Experimental study of commercial size proton exchange membrane fuel cell performance," Applied Energy, Elsevier, vol. 88(1), pages 392-396, January.
    4. Barelli, L. & Barluzzi, E. & Bidini, G. & Bonucci, F., 2012. "Cylinders diagnosis system of a 1MW internal combustion engine through vibrational signal processing using DWT technique," Applied Energy, Elsevier, vol. 92(C), pages 44-50.
    5. Rabbani, Abid & Rokni, Masoud, 2013. "Effect of nitrogen crossover on purging strategy in PEM fuel cell systems," Applied Energy, Elsevier, vol. 111(C), pages 1061-1070.
    6. 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.
    7. Wang, Yun & Chen, Ken S. & Mishler, Jeffrey & Cho, Sung Chan & Adroher, Xavier Cordobes, 2011. "A review of polymer electrolyte membrane fuel cells: Technology, applications, and needs on fundamental research," Applied Energy, Elsevier, vol. 88(4), pages 981-1007, April.
    8. Wang, Jian-Zhou & Wang, Yun & Jiang, Ping, 2015. "The study and application of a novel hybrid forecasting model – A case study of wind speed forecasting in China," Applied Energy, Elsevier, vol. 143(C), pages 472-488.
    9. da Fonseca, R. & Bideaux, E. & Gerard, M. & Jeanneret, B. & Desbois-Renaudin, M. & Sari, A., 2014. "Control of PEMFC system air group using differential flatness approach: Validation by a dynamic fuel cell system model," Applied Energy, Elsevier, vol. 113(C), pages 219-229.
    10. Meidanshahi, Vida & Karimi, Gholamreza, 2012. "Dynamic modeling, optimization and control of power density in a PEM fuel cell," Applied Energy, Elsevier, vol. 93(C), pages 98-105.
    11. Du, Zhimin & Jin, Xinqiao & Yang, Yunyu, 2009. "Fault diagnosis for temperature, flow rate and pressure sensors in VAV systems using wavelet neural network," Applied Energy, Elsevier, vol. 86(9), pages 1624-1631, September.
    12. Hosseinzadeh, Elham & Rokni, Masoud & Rabbani, Abid & Mortensen, Henrik Hilleke, 2013. "Thermal and water management of low temperature Proton Exchange Membrane Fuel Cell in fork-lift truck power system," Applied Energy, Elsevier, vol. 104(C), pages 434-444.
    13. Liu, Hui & Tian, Hong-qi & Pan, Di-fu & Li, Yan-fei, 2013. "Forecasting models for wind speed using wavelet, wavelet packet, time series and Artificial Neural Networks," Applied Energy, Elsevier, vol. 107(C), pages 191-208.
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    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. Wang, Zhenpo & Hong, Jichao & Liu, Peng & Zhang, Lei, 2017. "Voltage fault diagnosis and prognosis of battery systems based on entropy and Z-score for electric vehicles," Applied Energy, Elsevier, vol. 196(C), pages 289-302.
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    8. Sapountzoglou, Nikolaos & Lago, Jesus & De Schutter, Bart & Raison, Bertrand, 2020. "A generalizable and sensor-independent deep learning method for fault detection and location in low-voltage distribution grids," Applied Energy, Elsevier, vol. 276(C).
    9. 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).
    10. Logan Battrell & Aubree Trunkle & Erica Eggleton & Lifeng Zhang & Ryan Anderson, 2017. "Quantifying Cathode Water Transport via Anode Relative Humidity Measurements in a Polymer Electrolyte Membrane Fuel Cell," Energies, MDPI, vol. 10(8), pages 1-16, August.
    11. Feng Han & Ying Tian & Qiang Zou & Xin Zhang, 2020. "Research on the Fault Diagnosis of a Polymer Electrolyte Membrane Fuel Cell System," Energies, MDPI, vol. 13(10), pages 1-18, May.
    12. Shin, Donghoon & Yoo, Seungryeol, 2023. "Diagnostic method for PEM fuel cell states using probability Distribution-Based loss component analysis for voltage loss decomposition," Applied Energy, Elsevier, vol. 330(PB).
    13. 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.
    14. Pang, Ran & Zhang, Caizhi & Dai, Haifeng & Bai, Yunfeng & Hao, Dong & Chen, Jinrui & Zhang, Bin, 2022. "Intelligent health states recognition of fuel cell by cell voltage consistency under typical operating parameters," Applied Energy, Elsevier, vol. 305(C).
    15. Yu Zang & Wei Shangguan & Baigen Cai & Huashen Wang & Michael G Pecht, 2019. "Methods for fault diagnosis of high-speed railways: A review," Journal of Risk and Reliability, , vol. 233(5), pages 908-922, October.
    16. 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.

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