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Correlating variability of modeling parameters with cell performance: Monte Carlo simulation of a quasi-3D planar solid oxide fuel cell

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  • He, Zhongjie
  • Li, Hua
  • Birgersson, E.

Abstract

The performance of planar solid oxide fuel cells (P-SOFCs) depends on factors such as material properties, cell geometry, and operating conditions. This paper assesses the sensitivity of cell performance to individual and simultaneous effects of these factors. The analysis is based on Monte Carlo simulation (MCS) of a quasi-3D asymptotic spatially-smoothed (ASS) model, which can be applied to other types of fuel cells. The ASS model describes the leading-order physics in the PEN (positive electrode-electrolyte-negative electrode) structure and interconnects (including plain channels surrounded by solid ribs) of a 3D P-SOFC, and allows fast computation within half an hour for MCS with large sample sizes in orders of 103. 26 modeling parameters are varied in two scenarios to investigate the individual and simultaneous effects of the varying parameters on cell performance, respectively. The strength of the correlation between variations of parameters and cell performance are quantified and ranked, which provides information for cell optimization. Different ranks are obtained for the two scenarios and also for cases with different cell voltages or nominal operating temperatures. Extending the MCS of an ASS model for stack modeling is recommended.

Suggested Citation

  • He, Zhongjie & Li, Hua & Birgersson, E., 2016. "Correlating variability of modeling parameters with cell performance: Monte Carlo simulation of a quasi-3D planar solid oxide fuel cell," Renewable Energy, Elsevier, vol. 85(C), pages 1301-1315.
  • Handle: RePEc:eee:renene:v:85:y:2016:i:c:p:1301-1315
    DOI: 10.1016/j.renene.2015.07.050
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    References listed on IDEAS

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    1. He, Zhongjie & Birgersson, E. & Li, Hua, 2014. "Reduced non-isothermal model for the planar solid oxide fuel cell and stack," Energy, Elsevier, vol. 70(C), pages 478-492.
    2. Park, Joonguen & Kang, Juhyun & Bae, Joongmyeon, 2013. "Computational analysis of operating temperature, hydrogen flow rate and anode thickness in anode-supported flat-tube solid oxide fuel cells," Renewable Energy, Elsevier, vol. 54(C), pages 63-69.
    3. Unknown, 1992. "U.S. Tomato Statistics, 1960-90," Statistical Bulletin 154771, United States Department of Agriculture, Economic Research Service.
    4. He, Zhongjie & Li, Hua & Birgersson, E., 2014. "Correlating variability of modeling parameters with non-isothermal stack performance: Monte Carlo simulation of a portable 3D planar solid oxide fuel cell stack," Applied Energy, Elsevier, vol. 136(C), pages 560-575.
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    Cited by:

    1. Kannan, Vishvak & Xue, Hansong & Raman, K. Ashoke & Chen, Jiasheng & Fisher, Adrian & Birgersson, Erik, 2020. "Quantifying operating uncertainties of a PEMFC – Monte Carlo-machine learning based approach," Renewable Energy, Elsevier, vol. 158(C), pages 343-359.

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