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Because of multi-timescale characteristics and gas transmission delays, the thermal electrical cooperative control of solid oxide fuel cells is a complex and difficult issue. We have used modeling, analysis and optimization of a solid oxide fuel cell system control to guarantee a high efficiency and temperature safety during steady-state and power switch transients. An analysis-based optimization method that applies to discrete optimization problem with constraints is proposed to obtain optimal operating points with a maximum efficiency and to satisfy temperature constraints. Artificial neural-network models that were identified from a validated

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