Global sensitivity analysis of uncertain parameters based on 2D modeling of solid oxide fuel cell

In this study, we propose an enhanced quasi–two-dimensional and nonisothermal model for solid oxide fuel cell (SOFC) parametric simulation and optimization. The dependence of effective properties on microstructural parameters is fully considered in this model. Besides, an elementary effect (EE) approach based on Monte Carlo experiments is adopted to comprehensively evaluate the sensitivity of totally 24 parameters. A two sample Kolmogorov-Smirnov (K-S) test is carried out to evaluate the ability of EE method for robust and accurate sensitivity analysis. The investigation focuses on the important microstructural parameters of the composite anode/cathode function layers (AFL/CFL). With this research, relative volume fractions of conducting materials in the AFL/CFL are the most sensitive factors among all input parameters while particle radius is found to be the least sensitive microstructural parameters. The particle size ratio of electronic particles to ionic particles is found to be much more sensitive than particle size due to its significant effect on effective conductivity. The cathodic electrochemical parameters reflect cell performance more significantly than the anodic ones. To further elucidate the role of input factors, this study provides a principle for parametric sensitivity classification as well. Besides, impacts of current density variation on parametric sensitivity are comprehensively considered. Negative or positive effects of parameters on cell performance and their influencing mechanisms are also discussed. Furthermore, global sensitivity analysis for single parameters at different positions is performed to assess the probability of structural optimization along the channel length. Then, a feasible nonuniform distribution method in allusion to function layers is proposed for further improvement of cell performance according to global SA results of single parameters along the channel direction.