Multi-scale Modeling and Optimization of Polymer Electrolyte Fuel Cells

For achieving stringent design & performance objectives in energy systems, it becomes necessary to develop holistic integrated models as well as, ascertain the level of details required within each sub-system, for accurate physical description and system optimization. This requires multi-scale modeling, which involves description of atomistic, molecular, mesoscopic, continuum, device, and plant levels as well as transmitting information sequentially at each level to produce synergistic knowledge-bases. This dissertation focuses on constructing a generalized framework for integration, as well as examination of sensitivity of sub-system models to fulfill overall design & performance objectives by selecting hydrogen polymer electrolyte fuel cell (PEFC) as a benchmark case study. The hydrogen PEFC is an alternative power producing device for stationary and automotive applications, with advantages of high efficiency, operation on renewable fuels with near-zero green house gas emissions. We begin by developing an integrated modeling and optimization framework that includes detailed computational fluid dynamics based models. As an illustration, a multi-dimensional, multi-physics PEFC model is constructed