System-level monitoring and diagnosis of starvation faults in solid oxide electrolyzers

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This paper presents a model-based methodology for real-time fault detection in Solid Oxide Cells (SOCs), focusing on fuel-side starvation in electrolysis mode. Steam starvation occurs when consumption exceeds supply, while hydrogen starvation arises from an insufficient inlet fraction; both risking electrode degradation. With limited measurements, a lumped model with a square-root Unscented Kalman Filter is adopted to estimate gas partial pressures, stack temperature, and deviations from the nominal inlet fuel flow rate, using stack voltage, outlet air temperature, and outlet hydrogen flow rate measurements. Faults are flagged when the estimated states exceed adaptive thresholds derived from nominal predictions via moving-window filter. For quantification, the observer is augmented with two states capturing deviations in inlet steam and hydrogen flow rates. Furthermore, the total resistance is calculated: it increases under steam starvation and remains nearly unchanged under hydrogen starvation. Experimental validation confirms accurate, real-time detection and identification, helping achieve safer SOEC operation.

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