Abstract
An adjoint-space technique is presented for the large-scale optimization (i.e. optimization with over 102 design variables) of the catalyst distribution in fuel cells. The algorithm is based on evaluating the catalyst sensitivity functions of the discharge voltage under specified current conditions. The catalyst sensitivity functions are computed efficiently using a gradient maximization algorithm, which requires solving a small number of sparse linear systems of equations to find the Gâtaux derivatives of the discharge current of the cell with respect to the design variables. It is shown that the optimum distribution of the catalyst varies with the discharge conditions, with the positions of landings and openings, as well as with the geometry and dimensions of the layers. It should be noted that our numerical algorithm can be used to describe the complete profile of the optimal catalyst by providing the full (mathematically exact) distribution of platinum particles in the catalyst layer.
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