State estimation of exhaust valve position by Kalman Filter in PEM fuel cell systems

Sensitive systems in control approaches, such as fuel cells, require exact operating conditions for high efficiency, safety and endurance of the system. A promising method in controlling fuel cell systems is model predictive control (MPC). For those, many states have to be measured very precisely within high sampling rates, because they are used as initial values for the following calculations. However, some states, such as pressures, are more significant for the efficiency of the system than others. In case of incorrect measurements or general errors in operation, false outputs are calculated and damages can occur to the fuel cell. Therefore an estimation of significant system states is necessary to cover failures for avoiding negative influence on the system's efficiency. It is established that a powerful state estimator is the Kalman filter. In connection to nonlinear and constrained applications, such as fuel cell systems, different types of the Kalman filter have been proposed, e.g. Extended and Unscented Kalman filter (EKF, UKF). This paper deals with the state estimation of the exhaust valve position by use of an Unscented Kalman filter (UKF) to support the pressure control of a 4.4kW PEM fuel cell system.