This paper proposes a model-based approach for the fuel cell flooding diagnostics problem. The cathode channel flooding and the GDL flooding diagnostic problems are decoupled and formulated as standard joint state and parameter estimation problems, with the amounts of the liquid water treated as varying system parameters to be identified. The unscented Kalman Filter technique has been applied to solve these problems. Simulation results prove the applicability of the cascading unscented Kalman filter design for flooding diagnostics.

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