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Control of PEMFC system air group using differential flatness approach: Validation by a dynamic fuel cell system model

Author

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  • da Fonseca, R.
  • Bideaux, E.
  • Gerard, M.
  • Jeanneret, B.
  • Desbois-Renaudin, M.
  • Sari, A.

Abstract

In this paper, a non linear control strategy is applied to the air supply subsystem of a polymer electrode membrane fuel cell (PEMFC). Based on a simplified control model and using the differential flatness control theory, a controller is designed in order to regulate the most important variables in the air supply subsystem: the oxygen stoechiometry and the cathode pressure. Simulations are made using a very detailed model validated experimentally, which allows the evolution of different state variables in the stack to be observed during the power deliver operation. The simulation results show that the controller gives a good response in terms of performance, robustness and durability of the system, despite the dynamics power profiles demanded, the approximations made and the disturbances.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:113:y:2014:i:c:p:219-229
    DOI: 10.1016/j.apenergy.2013.07.043
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    References listed on IDEAS

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    1. Matraji, Imad & Laghrouche, Salah & Jemei, Samir & Wack, Maxime, 2013. "Robust control of the PEM fuel cell air-feed system via sub-optimal second order sliding mode," Applied Energy, Elsevier, vol. 104(C), pages 945-957.
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    3. Tirnovan, R. & Giurgea, S. & Miraoui, A., 2011. "Strategies for optimizing the opening of the outlet air circuit's nozzle to improve the efficiency of the PEMFC generator," Applied Energy, Elsevier, vol. 88(4), pages 1197-1204, April.
    4. Segura, Francisca & Andújar, José Manuel, 2012. "Power management based on sliding control applied to fuel cell systems: A further step towards the hybrid control concept," Applied Energy, Elsevier, vol. 99(C), pages 213-225.
    5. 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.
    6. Tang, Yong & Yuan, Wei & Pan, Minqiang & Wan, Zhenping, 2011. "Experimental investigation on the dynamic performance of a hybrid PEM fuel cell/battery system for lightweight electric vehicle application," Applied Energy, Elsevier, vol. 88(1), pages 68-76, January.
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    Cited by:

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    3. Han, Jaeyoung & Yu, Sangseok & Yi, Sun, 2017. "Adaptive control for robust air flow management in an automotive fuel cell system," Applied Energy, Elsevier, vol. 190(C), pages 73-83.
    4. Kim, Bosung & Cha, Dowon & Kim, Yongchan, 2015. "The effects of air stoichiometry and air excess ratio on the transient response of a PEMFC under load change conditions," Applied Energy, Elsevier, vol. 138(C), pages 143-149.
    5. Nicu Bizon & Mihai Oproescu, 2018. "Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control," Energies, MDPI, vol. 11(12), pages 1-32, December.
    6. Liu, Ze & Zhang, Baitao & Xu, Sichuan, 2022. "Research on air mass flow-pressure combined control and dynamic performance of fuel cell system for vehicles application," Applied Energy, Elsevier, vol. 309(C).
    7. Bizon, Nicu, 2014. "Tracking the maximum efficiency point for the FC system based on extremum seeking scheme to control the air flow," Applied Energy, Elsevier, vol. 129(C), pages 147-157.
    8. 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.
    9. 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.
    10. Xing, Lei & Das, Prodip K. & Song, Xueguan & Mamlouk, Mohamed & Scott, Keith, 2015. "Numerical analysis of the optimum membrane/ionomer water content of PEMFCs: The interaction of Nafion® ionomer content and cathode relative humidity," Applied Energy, Elsevier, vol. 138(C), pages 242-257.
    11. Li, Yuehua & Pei, Pucheng & Ma, Ze & Ren, Peng & Huang, Hao, 2020. "Analysis of air compression, progress of compressor and control for optimal energy efficiency in proton exchange membrane fuel cell," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
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    13. Martin Vrlić & Daniel Ritzberger & Stefan Jakubek, 2020. "Safe and Efficient Polymer Electrolyte Membrane Fuel Cell Control Using Successive Linearization Based Model Predictive Control Validated on Real Vehicle Data," Energies, MDPI, vol. 13(20), pages 1-16, October.
    14. Asensio, F.J. & San Martín, J.I. & Zamora, I. & Saldaña, G. & Oñederra, O., 2019. "Analysis of electrochemical and thermal models and modeling techniques for polymer electrolyte membrane fuel cells," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
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