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A Real-Time Dynamic Fuel Cell System Simulation for Model-Based Diagnostics and Control: Validation on Real Driving Data

Author

Listed:
  • Daniel Ritzberger

    (Institute of Mechanics and Mechatronics, TU-Wien, 1060 Vienna, Austria)

  • Christoph Hametner

    (Christian Doppler Laboratory for Innovative Control and Monitoring of Automotive Powertrain Systems, 1060 Vienna, Austria)

  • Stefan Jakubek

    (Institute of Mechanics and Mechatronics, TU-Wien, 1060 Vienna, Austria)

Abstract

Fuel cell systems are regarded as a promising candidate in replacing the internal combustion engine as a renewable and emission free alternative in automotive applications. However, the operation of a fuel cell stack fulfilling transient power-demands poses significant challenges. Efficiency is to be maximized while adhering to critical constraints, avoiding adverse operational conditions (fuel starvation, membrane flooding or drying, etc.) and mitigating degradation as to increase the life-time of the stack. Owing to this complexity, advanced model-based diagnostic and control methods are increasingly investigated. In this work, a real time stack model is presented and its experimental parameterization is discussed. Furthermore, the stack model is integrated in a system simulation, where the compressor dynamics, the feedback controls for the hydrogen injection and back-pressure valve actuation, and the purging strategy are considered. The resulting system simulation, driven by the set-point values of the operating strategy is evaluated and validated on experimental data obtained from a fuel cell vehicle during on-road operation. It will be shown how the internal states of the fuel cell simulation evolve during the transient operation of the fuel cell vehicle. The measurement data, for which this analysis is conducted, stem from a fuel cell research and demonstrator vehicle, developed by a consortium of several academic and industrial partners under the lead of AVL List GmbH.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3148-:d:372858
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    References listed on IDEAS

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    1. Priya, K. & Sathishkumar, K. & Rajasekar, N., 2018. "A comprehensive review on parameter estimation techniques for Proton Exchange Membrane fuel cell modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 121-144.
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    3. 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.
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    5. Das, Vipin & Padmanaban, Sanjeevikumar & Venkitusamy, Karthikeyan & Selvamuthukumaran, Rajasekar & Blaabjerg, Frede & Siano, Pierluigi, 2017. "Recent advances and challenges of fuel cell based power system architectures and control – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 10-18.
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    Cited by:

    1. Matthieu Matignon & Toufik Azib & Mehdi Mcharek & Ahmed Chaibet & Adriano Ceschia, 2023. "Real-Time Integrated Energy Management Strategy Applied to Fuel Cell Hybrid Systems," Energies, MDPI, vol. 16(6), pages 1-21, March.
    2. Martin Vrlić & Daniel Ritzberger & Stefan Jakubek, 2021. "Model-Predictive-Control-Based Reference Governor for Fuel Cells in Automotive Application Compared with Performance from a Real Vehicle," Energies, MDPI, vol. 14(8), pages 1-17, April.
    3. 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.
    4. Zhang Peng Du & Andraž Kravos & Christoph Steindl & Tomaž Katrašnik & Stefan Jakubek & Christoph Hametner, 2021. "Physically Motivated Water Modeling in Control-Oriented Polymer Electrolyte Membrane Fuel Cell Stack Models," Energies, MDPI, vol. 14(22), pages 1-20, November.
    5. Zili Wang & Guodong Yi & Shaoju Zhang, 2021. "An Improved Fuzzy PID Control Method Considering Hydrogen Fuel Cell Voltage-Output Characteristics for a Hydrogen Vehicle Power System," Energies, MDPI, vol. 14(19), pages 1-18, September.
    6. Tom Fletcher & Kambiz Ebrahimi, 2020. "The Effect of Fuel Cell and Battery Size on Efficiency and Cell Lifetime for an L7e Fuel Cell Hybrid Vehicle," Energies, MDPI, vol. 13(22), pages 1-18, November.

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