Parameter estimation of PEMFC system with unknown input

This paper presents the synthesis of a model-based robust observer with an unknown input that observes a state (manifold pressure) of Fuel Cell System (FCS) in the presence of uncertainties. Using this observer the proportionality constant of the inlet manifold orifice is estimated. Then this estimated parameter is used to calculate the time varying air mass flow. As the mass flow rates of reactant gases play a pivotal role in the reliable and efficient operation of FCS. Their precise and exact value is necessary and important for the control and diagnostics of FCS. In the particular sense of inlet manifold of fuel cell system, appropriate air mass flow is very critical for the proper maintenance of chemical reactions taking place in the cathode and anode chambers. The sliding mode observer (SMO) with super twisting algorithm is utilized for the estimation of the mass flow rate of air despite the unknown input (load current). The estimates come out to be quite close to the nominal values. The simulation results show robustness to the uncertainties and fast convergence of estimates to nominal values of the parameter. The chattering phenomenon is attenuated significantly by employing higher order sliding mode. The standard SMO results are also presented for the sake of comparison. The proposed strategy is useful for sensor reduction, fault diagnostics and control.