Collaborative control for power and temperature tracking of the solid oxide fuel cell under maximum system efficiency

Solid oxide fuel cell (SOFC) is a highly efficient and green power production technology with broad application prospects. The commercialization of the SOFC faces several control challenges, including load tracking, temperature safety, fuel starvation, and maximum efficiency. For solving these problems, a pre-reforming SOFC system model fueled by methane is first established and validated. Then, to optimize the efficiency of the system and find the relevant optimal operating points (OOPs) of the SOFC, a hybrid optimization approach that combines particle swarm optimization (PSO) with genetic algorithm (GA) is suggested. On this basis, an optimal thermo-electric coordination controller comprising OOPs feedforward controller, reference governor, and flow feedback controller is presented in this study. Simulation findings indicate the excellence of the presented cooperative control strategy for load power tracking and stack temperature control, while maximum efficiency, thermal safety and sufficient fuel are ensured.