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Modeling and temperature distribution estimation based on Kalman filter algorithm of a planar solid oxide fuel cell

To guarantee the thermal safety and obtain good performance of a solid oxide fuel cell (SOFC), the operating temperature and temperature gradient of SOFC must be constrained within a proper range. Thus, it's important to obtain the spatial temperature distribution of SOFC in real time. However, the inner temperature of the fuel cell cannot be obtained by installing thermocouples with acceptable cost for the strictly seal requirement of SOFC. In this paper, an observer based on Kalman filter algorithm is designed to estimate the inner temperature of the fuel cell with external easy-measured data. The observer design is based on a finite-volume parameter SOFC model. Before the observer design, the model is locally linearised on a steady operating point. Simulation results show that the designed observer can eliminate the initial errors quickly, estimate the spatial temperature distribution of SOFC rapidly and precisely, and is robust to the input disturbance of SOFC.