Solid Oxide Fuel Cells (SOFC) are high temperature energy converters. When an SOFC is operated for the rst time, a substantial increase in cell performance is observed which is caused by microstructural changes at the cathode/electrolyte interface. To optimize the resulting formation of the interface, a dynamic model is required that represents the relations between materials compositions, operating conditions, electric current, and microstructure.
Building a model based on chemical reaction equations fails because of the high complexity of the interface reactions. Therefore, this contribution presents an interdisciplinary approach to modeling in materials development by applying computational intelligence techniques. Qualitative models are used to formalize the expert knowledge about the irreversible materials changes at the cathode/electrolyte interface. Fuzzy if-then rules represent the dynamic behavior of the microstructural formation. The resulting model enables the application of simulations instead of time-consuming experiments and thus allows the systematic optimization of the startup process.