APPLICATION OF A SIGMA-POINT KALMAN-FILTER FOR THE ONLINE ESTIMATION OF FRACTIONAL ORDER IMPEDANCE MODELS FOR SOLID OXIDE FUEL CELLS

To operate a solid oxide fuel cell (SOFC) safely and efficiently, it is necessary to monitor the values of characteristic model parameters of the cell impedance. This paper addresses the problem to compute online-estimates of model parameters for SOFCs, whose impedance is represented by a fractional (non-integer) order impedance model. The fractional model of the impedance is approximated by a serial connection of a finite number of RC-elements. Assuming that the time-dependent model parameters of the impedance are treated as state-variables of an augmented state vector, the linearity-property is lost and the application of the classical linear Kalman-filter for state estimation is not longer possible. Hence, the so-called sigma-point Kalman-filter is used in order to solve this online estimation problem for nonlinear system dynamics. The feasibility and quality of this online identification approach is outlined by using simulated data with additional noise.