Development and experimental investigation of an extended Kalman filter for an industrial molten carbonate fuel cell system

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 Loève 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.