State estimation of a Molten Carbonate Fuel Cell by an Extended Kalman Filter

Abstract Industrial fuel cell stacks only provide very limited measurement information. To overcome this deficit, a state estimator for a molten carbonate fuel cell system is developed in this contribution. The starting point of the work is a rigorous spatially distributed model of the system. From this model a reduced model is derived by using a Galerkin method and the Karhunen Loeve decomposition technique. An extended Kalman filter with a continuous time simulator part and a discrete time corrector part is designed on the basis of the reduced model. The filter is tested in simulations and experimentally.