Inverse estimation of electrode microstructure distributions in NASA Bi-electrode supported solid oxide fuel cells

The uniqueness of NASA bi-electrode supported cell (BSC) is the functionally graded porous electrodes fabricated using freeze tape casting technique. Quantitative characterization of electrode microstructure distributions is a critical step towards model validation and numerical analysis. In this paper, a computational fluid dynamic (CFD) based multi-physicochemical model is adapted according to the BSC experimental setup. An inverse method with genetic algorithm is developed to estimate the porosity and pore size distributions of the electrodes by matching the model predictions with the experimental results in terms of polarization performance. The inverse method is verified using the simulated results and employed for the estimation of practical electrode porous microstructure distributions. The results indicate that the polarization performance predictions with identified porous microstructure distributions match pretty well with the experimental results under several temperature conditions simultaneously. This research provides a novel method for porous electrode quantification.

► Multi-physicochemical model is developed according to the BSC experimental setup. ► Functionally graded porous electrodes are linked to polarization performance. ► An inverse method is developed to estimate graded porosity and pore size of BSC.