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

Zhongjie He, Hua Li and E. Birgersson

Renewable Energy, 2016, vol. 85, issue C, 1301-1315

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.

Keywords: Monte Carlo simulation; Quasi-3D; Sensitivity analysis; Solid oxide fuel cell (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:85:y:2016:i:c:p:1301-1315

DOI: 10.1016/j.renene.2015.07.050

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