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Experimental real-time optimization of a solid oxide fuel cell stack via constraint adaptation

Bunin, Gene A., Wuillemin, Zacharie, François, Grégory, Nakajo, Arata, Tsikonis, Leonidas, Bonvin, Dominique
Energy 2012 v.39 no.1 pp. 54-62
algorithms, fuel cells, methodology, models
The experimental validation of a real-time optimization (RTO) strategy for the optimal operation of a solid oxide fuel cell (SOFC) stack is reported in this paper. Unlike many existing studies, the RTO approach presented here utilizes the constraint-adaptation methodology, which assumes that the optimal operating point lies on a set of active constraints and then seeks to satisfy those constraints in practice via the addition of a correction term to each constraint function. These correction terms, also referred to as “modifiers”, correspond to the difference between predicted and measured constraint values and are updated at each steady-state iteration, thereby allowing the RTO to iteratively meet the optimal operating conditions of an SOFC stack despite significant plant-model mismatch. The effects of the filter parameters used in the modifier update and of the RTO frequency on the general performance of the algorithm are also investigated.