On-line Tracking of Fuel Cell System Impedance Using Extended Kalman Filter

This paper presents a new measurement equipment and computational method for on-line estimation and tracking of PEM fuel cell system impedance. The algorithm is developed to address one of the main issues influencing the reliability and durability of PEM fuel cell technology - the water management in fuel cell stacks, namely fuel cell flooding and membrane drying. Using the appropriate model formulation and system state variables, the model allows direct estimation of the characteristic values of the fuel cell impedance at different frequencies and thus avoids the need for transformation of the measured signals to the frequency domain. Estimation of the model state variables is performed with Extended Kalman filter, which is renowned for its computational efficiency, while the probabilistic interpretation of the algorithm ensures adequate management of the uncertainties. The performance of the diagnostic system is explored on experimental data from a commercial fuel cell stack consisting of 80 fuel cells.