Microscale Correlations Adoption in Solid Oxide Fuel Cell

Abstract

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.