Dynamic Analysis of Planar Solid Oxide Fuel Cell Models With Different Assumptions of Temperature Layers

As solid oxide fuel cell (SOFC) technology is rapidly evolving, high-fidelity mathematical models based on physical principles have become essential tools for SOFC system design and analysis. While several SOFC models have been developed by different groups using different modeling assumptions, little analysis of the effects of these assumptions on model performance can be found in literature. Meanwhile, to support system optimization and control design activities, a trade-off often has to be made between high fidelity and low complexity. This trade-off can be influenced by the number of temperature layers assumed in the energy balance to represent the SOFC structure. In this paper, we investigate the impact of the temperature layer assumption on the performance of the dynamic planar SOFC model. Four models of co-flow planar SOFCs are derived using the finite volume discretization approach along with different assumptions in the number of temperature layers. The model with four temperature layers is used as the baseline model, and the other models aimed at reducing the complexity of the baseline model are developed and compared through simulations as well as linear analysis. We show that the model with as few as two temperature layers-the solid structure and air bulk flow-is able to capture the dynamics of SOFCs, while assuming only one temperature layer results in significantly large modeling error.