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A macroscopic PEM fuel cell model including water phenomena for vehicle simulation

Author

Listed:
  • Boulon, L.
  • Agbossou, K.
  • Hissel, D.
  • Sicard, P.
  • Bouscayrol, A.
  • Péra, M.-C.

Abstract

This paper presents a Proton Exchange Membrane Fuel Cell model suitable for water management analysis. In order to be integrated into a complete fuel cell vehicle simulation for real-time control and energy management designs, Energetic Macroscopic Representation is used. An experimental validation is performed and electric and gaseous behaviors are studied in particular. The integration of the developed model into a vehicle simulation, in which the FC is used as a range extender, demonstrates the use of the model and allows the study of the behavior of this system.

Suggested Citation

  • Boulon, L. & Agbossou, K. & Hissel, D. & Sicard, P. & Bouscayrol, A. & Péra, M.-C., 2012. "A macroscopic PEM fuel cell model including water phenomena for vehicle simulation," Renewable Energy, Elsevier, vol. 46(C), pages 81-91.
    • Handle: RePEc:eee:renene:v:46:y:2012:i:c:p:81-91
    DOI: 10.1016/j.renene.2012.03.009
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    References listed on IDEAS

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    1. Tavakoli, B. & Roshandel, R., 2011. "The effect of fuel cell operational conditions on the water content distribution in the polymer electrolyte membrane," Renewable Energy, Elsevier, vol. 36(12), pages 3319-3331.
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    Cited by:

    1. Colmenar-Santos, Antonio & Alberdi-Jiménez, Lucía & Nasarre-Cortés, Lorenzo & Mora-Larramona, Joaquín, 2014. "Residual heat use generated by a 12 kW fuel cell in an electric vehicle heating system," Energy, Elsevier, vol. 68(C), pages 182-190.
    2. Daniel Ritzberger & Christoph Hametner & Stefan Jakubek, 2020. "A Real-Time Dynamic Fuel Cell System Simulation for Model-Based Diagnostics and Control: Validation on Real Driving Data," Energies, MDPI, vol. 13(12), pages 1-20, June.
    3. Deng, Hao & Wang, Dawei & Xie, Xu & Zhou, Yibo & Yin, Yan & Du, Qing & Jiao, Kui, 2016. "Modeling of hydrogen alkaline membrane fuel cell with interfacial effect and water management optimization," Renewable Energy, Elsevier, vol. 91(C), pages 166-177.
    4. Gregor Tavčar & Tomaž Katrašnik, 2013. "An Innovative Hybrid 3D Analytic-Numerical Approach for System Level Modelling of PEM Fuel Cells," Energies, MDPI, vol. 6(10), pages 1-60, October.
    5. Chen, Kui & Laghrouche, Salah & Djerdir, Abdesslem, 2021. "Prognosis of fuel cell degradation under different applications using wavelet analysis and nonlinear autoregressive exogenous neural network," Renewable Energy, Elsevier, vol. 179(C), pages 802-814.
    6. Tiejiang Yuan & Qingxi Duan & Xiangping Chen & Xufeng Yuan & Wenping Cao & Juan Hu & Quanmin Zhu, 2017. "Coordinated Control of a Wind-Methanol-Fuel Cell System with Hydrogen Storage," Energies, MDPI, vol. 10(12), pages 1-21, December.
    7. Lopez Lopez, Guadalupe & Schacht Rodriguez, Ricardo & Alvarado, Victor M. & Gomez-Aguilar, J.F. & Mota, Juan E. & Sandoval, Cinda, 2017. "Hybrid PEMFC-supercapacitor system: Modeling and energy management in energetic macroscopic representation," Applied Energy, Elsevier, vol. 205(C), pages 1478-1494.
    8. Yuan, Xueliang & Liu, Xin & Zuo, Jian, 2015. "The development of new energy vehicles for a sustainable future: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 298-305.

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