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This new fuel cell stack diagnostics technology utilizes a signal distortion analysis to determine the actual status of a fuel cell / fuel cell stack in terms of critical operation conditions. Oxygen and hydrogen starvation, cell floodings are detectable with this method. In this paper the results of a flooding situation and an air starvation case are discussed. Also a semi empirical model is described which enables the prediction of the cell behavior in such critical operation modes.