(143e) Fuel Cell System Integration Via Reduced Order Methods
In integrating multi-component system models, such as polymer electrolyte fuel cells (PEFCs), situations often arise where information for one or more sub-components is not fully available; nor is direct integration among the disparate sub-components (especially in multi-scale systems) trivial. In these cases, one novel methodology for achieving system integration is to capture very complex sub-system information via simple parametric representations, yet keeping the essence of the physics. In this study, we explore whether such compact mathematical representations of the missing information exist.
We recently developed an agglomerate catalyst layer (CL) model  connected with the gas diffusion layer (GDL) sub-component of the PEFC, and linked the resulting nonlinear partial differential algebraic equations capturing the essential transport and reaction processes, to a state-of-the-art interior point optimization algorithm, IPOPT . For the integrated PEFC system without fully examining the three-dimensional governing equations of the gas channel (GC) sub-component, we mimicked the GC effect to the neighboring GDL via two-dimensional parametric boundary conditions at the outer surface of the GC. We have extensively studied the solution and optimization properties by systematically tuning the degree of non-homogeneity in the GC/GDL interface boundary.
We obtained the above benchmark PEFC system analysis to replace unknown sub-component system with manageable number of parameters, termed as a reduced order method (ROM), and obtained approximate results in extremely short computational times. This ROM will be extended to several unknown systems; by using these ideas we can easily link two different sub-systems with reduced number of parameters in conjunction with system optimization. Further, extension of integrating multi-scale systems using ROM will be given.
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