IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v6y2013i10p5426-5485d29729.html
   My bibliography  Save this article

An Innovative Hybrid 3D Analytic-Numerical Approach for System Level Modelling of PEM Fuel Cells

Author

Listed:
  • Gregor Tavčar

    (University of Ljubljana, Faculty of Mechanical Engineering, Aškerčeva 6, Ljubljana SI-1000, Slovenia)

  • Tomaž Katrašnik

    (University of Ljubljana, Faculty of Mechanical Engineering, Aškerčeva 6, Ljubljana SI-1000, Slovenia)

Abstract

The PEM fuel cell model presented in this paper is based on modelling species transport and coupling electrochemical reactions to species transport in an innovative way. Species transport is modelled by obtaining a 2D analytic solution for species concentration distribution in the plane perpendicular to the gas-flow and coupling consecutive 2D solutions by means of a 1D numerical gas-flow model. The 2D solution is devised on a jigsaw puzzle of multiple coupled domains which enables the modelling of parallel straight channel fuel cells with realistic geometries. Electrochemical and other nonlinear phenomena are coupled to the species transport by a routine that uses derivative approximation with prediction-iteration. A hybrid 3D analytic-numerical fuel cell model of a laboratory test fuel cell is presented and evaluated against a professional 3D computational fluid dynamic (CFD) simulation tool. This comparative evaluation shows very good agreement between results of the presented model and those of the CFD simulation. Furthermore, high accuracy results are achieved at computational times short enough to be suitable for system level simulations. This computational efficiency is owed to the semi-analytic nature of its species transport modelling and to the efficient computational coupling of electrochemical kinetics and species transport.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:6:y:2013:i:10:p:5426-5485:d:29729
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/6/10/5426/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/6/10/5426/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Pathapati, P.R. & Xue, X. & Tang, J., 2005. "A new dynamic model for predicting transient phenomena in a PEM fuel cell system," Renewable Energy, Elsevier, vol. 30(1), pages 1-22.
    3. Melika Hinaje & Stéphane Raël & Panee Noiying & Dinh An Nguyen & Bernard Davat, 2012. "An Equivalent Electrical Circuit Model of Proton Exchange Membrane Fuel Cells Based on Mathematical Modelling," Energies, MDPI, vol. 5(8), pages 1-21, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Hou, Yongping & Yang, Zhihua & Fang, Xue, 2011. "An experimental study on the dynamic process of PEM fuel cell stack voltage," Renewable Energy, Elsevier, vol. 36(1), pages 325-329.
    3. Scrivano, G. & Piacentino, A. & Cardona, F., 2009. "Experimental characterization of PEM fuel cells by micro-models for the prediction of on-site performance," Renewable Energy, Elsevier, vol. 34(3), pages 634-639.
    4. Sharifi Asl, S.M. & Rowshanzamir, S. & Eikani, M.H., 2010. "Modelling and simulation of the steady-state and dynamic behaviour of a PEM fuel cell," Energy, Elsevier, vol. 35(4), pages 1633-1646.
    5. Damien Guilbert & Gianpaolo Vitale, 2019. "Dynamic Emulation of a PEM Electrolyzer by Time Constant Based Exponential Model," Energies, MDPI, vol. 12(4), pages 1-17, February.
    6. Deng, Zhihua & Chen, Qihong & Zhang, Liyan & Zhou, Keliang & Zong, Yi & Fu, Zhichao & Liu, Hao, 2021. "Data-driven reconstruction of interpretable model for air supply system of proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 299(C).
    7. 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.
    8. Hao Huang & Hua Ding & Donghai Hu & Zhaoxu Cheng & Chengyun Qiu & Yuran Shen & Xiangwen Su, 2023. "Thermal Performance Optimization of Multiple Circuits Cooling System for Fuel Cell Vehicle," Sustainability, MDPI, vol. 15(4), pages 1-23, February.
    9. Sutharssan, Thamo & Montalvao, Diogo & Chen, Yong Kang & Wang, Wen-Chung & Pisac, Claudia & Elemara, Hakim, 2017. "A review on prognostics and health monitoring of proton exchange membrane fuel cell," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 440-450.
    10. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah & Parastegari, Moein, 2019. "An efficient scenario-based stochastic programming method for optimal scheduling of CHP-PEMFC, WT, PV and hydrogen storage units in micro grids," Renewable Energy, Elsevier, vol. 130(C), pages 1049-1066.
    11. 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.
    12. Shao, Meng & Zhu, Xin-Jian & Cao, Hong-Fei & Shen, Hai-Feng, 2014. "An artificial neural network ensemble method for fault diagnosis of proton exchange membrane fuel cell system," Energy, Elsevier, vol. 67(C), pages 268-275.
    13. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah & Khodabakhshian, Amin & Parastegari, Moein, 2017. "Optimal stochastic coordinated scheduling of proton exchange membrane fuel cell-combined heat and power, wind and photovoltaic units in micro grids considering hydrogen storage," Applied Energy, Elsevier, vol. 202(C), pages 308-322.
    14. Long-Yi Chang & Hung-Cheng Chen, 2014. "Linearization and Input-Output Decoupling for Nonlinear Control of Proton Exchange Membrane Fuel Cells," Energies, MDPI, vol. 7(2), pages 1-16, January.
    15. Milos Milanovic & Verica Radisavljevic-Gajic, 2019. "Multi-Timescale-Based Partial Optimal Control of a Proton-Exchange Membrane Fuel Cell," Energies, MDPI, vol. 13(1), pages 1-24, December.
    16. 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.
    17. Mahmoud S. AbouOmar & Hua-Jun Zhang & Yi-Xin Su, 2019. "Fractional Order Fuzzy PID Control of Automotive PEM Fuel Cell Air Feed System Using Neural Network Optimization Algorithm," Energies, MDPI, vol. 12(8), pages 1-23, April.
    18. Hwang, Jenn-Jiang, 2013. "Thermal control and performance assessment of a proton exchanger membrane fuel cell generator," Applied Energy, Elsevier, vol. 108(C), pages 184-193.
    19. Hou, Yongping & Shen, Caoyuan & Hao, Dong & Liu, Yanan & Wang, Hong, 2014. "A dynamic model for hydrogen consumption of fuel cell stacks considering the effects of hydrogen purge operation," Renewable Energy, Elsevier, vol. 62(C), pages 672-678.
    20. Elena Crespi & Giulio Guandalini & German Nieto Cantero & Stefano Campanari, 2022. "Dynamic Modeling of a PEM Fuel Cell Power Plant for Flexibility Optimization and Grid Support," Energies, MDPI, vol. 15(13), pages 1-23, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:6:y:2013:i:10:p:5426-5485:d:29729. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.