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In this paper, we address the problem of online parameter estimation of aProton Exchange Membrane Fuel Cell (PEMFC) polarization curve, that is thestatic relation between the voltage and the current of the PEMFC. The task ofdesigning this estimator -- even off-line -- is complicated by the fact thatthe uncertain parameters enter the curve in a highly nonlinear fashion, namelyin the form of nonseparable nonlinearities. We consider several scenarios forthe model of the polarization curve, starting from the standard full model andincluding several popular simplifications to this complicated mathematicalfunction. In all cases, we derive separable regression equations -- eitherlinearly or nonlinearly parameterized -- which are instrumental for theimplementation of the parameter estimators. We concentrate our attention onon-line estimation schemes for which, under suitable excitation conditions,global parameter convergence is ensured. Due to these global convergenceproperties, the estimators are robust to unavoidable additive noise andstructural uncertainty. Moreover, their on-line nature endows the schemes withthe ability to track (slow) parameter variations, that occur during theoperation of the PEMFC. These two features -- unavailable in time-consumingoff-line data-fitting procedures -- make the proposed estimators helpful foron-line time-saving characterization of a given PEMFC, and the implementationof fault-detection procedures and model-based adaptive control strategies.Simulation and experimental results that validate the theoretical claims arepresented.

On-line Parameter Estimation of the Polarization Curve of a Fuel Cell with Guaranteed Convergence Properties: Theoretical and Experimental Results