Fault Diagnosis of PEM Fuel Cell

  • Andres Hernandez
  • Rachid Outbib
  • Daniel Hissel
Part of the Green Energy and Technology book series (GREEN)


This chapter deals with the problem of fault diagnosis for proton exchange membrane fuel cells (PEMFC). The goal is to present two strategies for fault diagnosis that are based, respectively, on the electrical equivalent technical and statistical approaches. The first strategy is carried out in two steps. First, an electrical equivalent model, which could be considered as a unifying approach to fuel cell systems, is established. Second, a technical approach to use the electrical model, for fuel cell system diagnosis, will be introduced. The second strategy is based on information from fuel cell conditions and operation modes. This makes the fault diagnosis procedure simpler and can be achieved by considering probability density functions of cell voltage. In this work, the main failure considered is flooding. To illustrate the performances of the two proposed approaches, experimental validations of the model and the diagnosis methodology are given.


Fuel Cell Liquid Water Fault Diagnosis Cell Voltage Saturation Pressure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Kozlowski JD, Byington CS, Garga AK, Watson MJ, Hay TA (2002) Model-based predictive diagnostics for electrochemical energy sources. In: Aerospace conference, 2001, IEEE Proceedings, vol 6. IEEE, pp 3149–3164Google Scholar
  2. 2.
    Burford D, Davis T, Mench MM (2004) Real-time electrolyte temperature measurement in an operating polymer electrolyte fuel cell. In: Adv Mater Fuel Cells Batteries SympGoogle Scholar
  3. 3.
    Hissel D, Péra MC, Kauffmann JM (2004) Diagnosis of automotive fuel cell power generators. J Power Sources 128(2):239–246CrossRefGoogle Scholar
  4. 4.
    Nitsche C, Schroedl S, Weiss W (2004) Onboard diagnostics concept for fuel cell vehicles using adaptive modelling. In:Intelligent Vehicles Symposium, 2004 IEEE. IEEE, pp 127–132Google Scholar
  5. 5.
    Brunetto C, Tina G, Squadrito G, Moschetto A (2004) PEMFC diagnostics and modelling by electrochemical impedance spectroscopy. In: Electrotechnical conference, 2004. MELECON 2004. Proceedings of the 12th IEEE Mediterranean, vol 3. IEEE, pp 1045–1050Google Scholar
  6. 6.
    Tsujioku Y, Iwase M, Hatakeyama S (2005) Analysis and modeling of a direct methanol fuel cell for failure diagnosis. In: Industrial electronics society, 2004. IECON 2004. 30th Annual Conference of IEEE, vol 3. IEEE, pp 2837–2842Google Scholar
  7. 7.
    Hernandez A, Hissel D, Outbib R (2010) Modeling and fault diagnosis of a polymer electrolyte fuel cell Using electrical equivalent analysis. . Energy Convers, IEEE Trans on 25(1):148–160CrossRefGoogle Scholar
  8. 8.
    Hernandez A, Hissel D, Outbib R (2006) Non linear state space modelling of a PEMFC. Fuel Cells 6(1):38–46CrossRefGoogle Scholar
  9. 9.
    Pekula N, Heller K, Chuang PA, Turhan A, Mench MM, Brenizer JS, Ünlü K (2005) Study of water distribution and transport in a polymer electrolyte fuel cell using neutron imaging. Nucl Instrum Methods Phys Res Section A: Accel Spectrom Detect Assoc Equip 542(1–3):134–141CrossRefGoogle Scholar
  10. 10.
    Hernandez E, Diong B (2005) A small-signal equivalent circuit model for PEM fuel cells. In: Applied power electronics conference and exposition, 2005. APEC 2005. Twentieth Annual IEEE,vol 1. IEEE, pp 121–126Google Scholar
  11. 11.
    Famouri P, Gemmen RS (2004) Electrochemical circuit model of a PEM fuel cell. In: Power engineering society general meeting, 2003, IEEE, vol 3. IEEEGoogle Scholar
  12. 12.
    Yu D, Yuvarajan S (2005) A novel circuit model for PEM fuel cells. In: Applied power electronics conference and exposition, 2004. APEC’04. Nineteenth Annual IEEE, vol 1. IEEE, pp 362–366Google Scholar
  13. 13.
    Jung A (2002) A mathematical model of the hydrodynamical processes in the brain. In: Und N(ed) Nichtgleichgewicht in kondensierter Materie, Workshop Report IIGoogle Scholar
  14. 14.
    Kerr R (2005) Fundamental fluidmechanics. In: Lectures for es30a/d, University of WarwickGoogle Scholar
  15. 15.
    Pukrushpan JT, Peng H, Stefanopoulou AG (2002) Simulation and analysis of transient fuel cell system performance based on a dynamic reactant flow model. In: Proceedings of 2002 ASME, Nov International mechanical engineering congress & exposition, pp 17–22Google Scholar
  16. 16.
    Pukrushpan J, Peng H, Stefanopoulou A (2004) Control-oriented modelling and analysis for automotive fuel cell systems. J Dyn Syst 126:14–25Google Scholar
  17. 17.
    Nguyen TV, White RE (1993) A water and heat management model for proton-exchange-membrane fuel cells. J Electrochem Soc 140:2178CrossRefGoogle Scholar
  18. 18.
    ASAE. Psychometric Data SAE D271.2. American Society of Agricultural Standard, 1999Google Scholar
  19. 19.
    Yerramalla S, Davari A, Feliachi A, Biswas T (2003) Modeling and simulation of the dynamic behavior of a polymer electrolyte membrane fuel cell. J Power Sources 124(1):104–113CrossRefGoogle Scholar
  20. 20.
    Golbert J, Lewin D (2004) Model-based control of fuel cells: (1) regulatory control. J Power Sources 135:135–151CrossRefGoogle Scholar
  21. 21.
    Maggio G, Recupero V, Pino L (2001) Modeling polymer electrolyte fuel cells: an innovative approach. J Power Sources 101(2):275–286CrossRefGoogle Scholar
  22. 22.
    Natarajan D, Van Nguyen T (2003) Three-dimensional effects of liquid water flooding in the cathode of a PEM fuel cell. J Power Sources 115(1):66–80CrossRefGoogle Scholar
  23. 23.
    Hernandez A, Diagnostic d’une pile à combustible de type PEFC. PhD thesis, Université de Technologie de Belfort-Montbéliard (UTBM)Google Scholar
  24. 24.
    Fang G, Ward CA (1999) Examination of the statistical rate theory expression for liquid evaporation rates. Phys Rev E 59(1):441–453CrossRefGoogle Scholar
  25. 25.
    Correa JM, Farret FA, Popov VB, Parizzi JB (2004) Influence of the modeling parameters on the simulation accuracy of proton exchange membrane fuel cells. In: Power tech conference proceedings, 2003 IEEE Bologna, vol 2. IEEE, p 8Google Scholar

Copyright information

© Springer-Verlag London Limited  2012

Authors and Affiliations

  • Andres Hernandez
    • 2
  • Rachid Outbib
    • 1
  • Daniel Hissel
    • 3
  1. 1.LSIS, Aix-Marseille UniversityMarseillesFrance
  2. 2.Escuela Colombiana de Ingeniería JulioGaravitoColombia
  3. 3.FEMTO-FClabBelfort cedexFrance

Personalised recommendations