Performance optimization of a solid oxide fuel cell system for long-term operation

Optimizing long-term operation of solid oxide fuel cell (SOFC) systems while preserving efficiency and durability remains challenging under time-varying demand. This work addresses two open problems: the absence of robust end-of-life (EoL) criteria under dynamic conditions and limited system-level supervisory optimization over realistic demand profiles. A framework combining an empirically calibrated degradation model, a dynamic system model, and supervisory optimization is applied to a real SOFC system. Three strategies (fixed power, voltage, and temperature) are evaluated under standard operation, degradation rate minimization, and efficiency maximization. Voltage- and power-based EoL criteria prove unreliable under constraint-driven operating-point shifts; cumulative energy, grounded in a discounted-cost consistency check, provides a robust alternative. Stack temperature dominates degradation control over current density and fuel utilization. Applied to a Swiss building demand profile, degradation-minimized control raises average efficiency by 6.2% while halving cumulative energy degradation, with no electrical efficiency-lifetime trade-off. By minimizing degradation, simulated lifetime increases severalfold.