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Research Papers

Microscale Correlations Adoption in Solid Oxide Fuel Cell

[+] Author and Article Information
C. Wang

Mechanical and Materials
Engineering Department,
Wright State University,
3640 Colonel Glenn Highway,
Dayton, OH 45435
e-mail: chao.wang@wright.edu

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF FUEL CELL SCIENCE AND TECHNOLOGY. Manuscript received December 16, 2014; final manuscript received July 21, 2015; published online August 18, 2015. Assoc. Editor: Dr Masashi Mori.

J. Fuel Cell Sci. Technol 12(4), 041006 (Aug 18, 2015) (11 pages) Paper No: FC-14-1147; doi: 10.1115/1.4031153 History: Received December 16, 2014; Revised July 21, 2015

In order to develop a predictive model of real cell performance, firm relationships and assumptions need to be established for the definition of the physical and microstructure parameters for solid oxide fuel cells (SOFCs). This study explores the correlations of microstructure parameters from a microscale level, together with mass transfer and electrochemical reactions inside the electrodes, providing a novel approach to predict SOFC performance numerically. Based on the physical connections and interactions of microstructure parameters, two submodel correlations (i.e., porosity–tortuosity and porosity–particle size ratio) are proposed. Three experiments from literature are selected to facilitate the validation of the numerical results with experimental data. In addition, a sensitivity analysis is performed to investigate the impact of the adopted submodel correlations to the SOFC performance predictions. Normally, the microstructural inputs in the numerical model need to be measured by experiments in order to test the real cell performance. By adopting the two submodel correlations, the simulation can be performed without obtaining relatively hard-to-measure microstructural parameters such as tortuosity and particle size, yet still accurately mimicking a real-world well-structured SOFC operation. By accurately and rationally predicting the microstructural parameters, this study can eventually help to aid the experimental and optimization study of SOFC.

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References

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Figures

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Fig. 1

Percolation threshold in the electrode

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Fig. 2

Anode computational domain

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Fig. 3

Dependence of tortuosity on the packing porosity [9]

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Fig. 8

SEM picture of Ni/8 mol. % Y2O3–ZrO2 (Ni/TZ8Y) cermet anodes sintered at (a) 1300 °C, (b) 1350 °C, (c) 1400 °C, and (d) 1500 °C. (Reprinted with permission from Jiang [21]. Copyright 2003 by Journal of the Electrochemical Society.)

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Fig. 7

Comparison between numerical results and experimental data for case no. 2 [20]

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Fig. 6

Comparison between numerical results and experimental data for case no. 1 [19]

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Fig. 5

Packing density versus composition for different particle size ratios [18]

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Fig. 4

Dependence of n on φL for different particle size ratios [10]

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Fig. 9

Comparison between numerical results and experimental data for case no. 3 [21]

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Fig. 10

Comparison of predicted anode overpotential at different n-values

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Fig. 11

Effect of particle size ratio on active surface area

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Fig. 12

Comparison of predicted anode overpotential at different particle size ratio values

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