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A Surrogate Model of the Butler-Volmer Equation for the Prediction of Thermodynamic Losses of Solid Oxide Fuel Cell Electrode

Author

Listed:
  • Szymon Buchaniec

    (Department of Fundamental Research in Energy Engineering, AGH University of Krakow, 30-059 Krakow, Poland)

  • Marek Gnatowski

    (Department of Fundamental Research in Energy Engineering, AGH University of Krakow, 30-059 Krakow, Poland)

  • Hiroshi Hasegawa

    (Department of Machinery and Control Systems, Shibaura Institute of Technology, Tokyo 135-8548, Japan)

  • Grzegorz Brus

    (Department of Fundamental Research in Energy Engineering, AGH University of Krakow, 30-059 Krakow, Poland)

Abstract

Solid oxide fuel cells are becoming increasingly important in various applications, from households to large-scale power plants. However, these electrochemical energy conversion devices have complex behavior that is difficult to understand and optimize. A numerical simulation is a primary tool for analysis and optimization-design. One of the most significant challenges in this field is improving microscale transport phenomena and electrode reaction models. Two main categories of simulation are black-box and white-box models. The former requires large experimental datasets and lacks physical constraints, while the latter inherits the inaccuracy of typical electrochemical reaction models. Here we show a micro-scale artificial neural network-supported numerical simulation that allows for overcoming those issues. In our research, we substituted one equation in the system, an electrochemical model, with an artificial neural network prediction. The data-driven prediction is constrained and must satisfy all reminded balance equations in the system. The results show that the proposed model can simulate an anode-electrode’s thermodynamic losses with improved accuracy compared with the classical approach. The coefficient of determination R 2 for the proposed model was equal to 0.8810 for 800 °C, 0.8720 for 900 °C, and 0.8436 for 1000 °C. The findings open a way for improving the accuracy and computational complexity of electrochemical models in solid oxide fuel cell simulations.

Suggested Citation

  • Szymon Buchaniec & Marek Gnatowski & Hiroshi Hasegawa & Grzegorz Brus, 2023. "A Surrogate Model of the Butler-Volmer Equation for the Prediction of Thermodynamic Losses of Solid Oxide Fuel Cell Electrode," Energies, MDPI, vol. 16(15), pages 1-12, July.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:15:p:5651-:d:1203960
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    References listed on IDEAS

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    1. Xu, Haoran & Chen, Bin & Tan, Peng & Cai, Weizi & He, Wei & Farrusseng, David & Ni, Meng, 2018. "Modeling of all porous solid oxide fuel cells," Applied Energy, Elsevier, vol. 219(C), pages 105-113.
    2. Szymon Buchaniec & Marek Gnatowski & Grzegorz Brus, 2021. "Integration of Classical Mathematical Modeling with an Artificial Neural Network for the Problems with Limited Dataset," Energies, MDPI, vol. 14(16), pages 1-23, August.
    3. Tomasz A. Prokop & Grzegorz Brus & Shinji Kimijima & Janusz S. Szmyd, 2020. "Thin Solid Film Electrolyte and Its Impact on Electrode Polarization in Solid Oxide Fuel Cells Studied by Three-Dimensional Microstructure-Scale Numerical Simulation," Energies, MDPI, vol. 13(19), pages 1-14, October.
    4. Karol K. Śreniawski & Marcin Moździerz & Grzegorz Brus & Janusz S. Szmyd, 2023. "Transport Phenomena in a Banded Solid Oxide Fuel Cell Stack—Part 2: Numerical Analysis," Energies, MDPI, vol. 16(11), pages 1-21, June.
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