On the implementation of an adaptive extremum seeking algorithm for hydrogen minimization in PEM fuel cell based systems

This work presents initial experimental results of an adaptive sliding-mode extremum seeker that minimizes the hydrogen consumption in a fuel cell based system. The extremum seeker is based on the classical steepest-descent method, the main challenge being the fact that the gradient of the objective function is unknown. The gradient is estimated by means of a sliding-mode adaptive estimator. The strategy is applied in experimental practical situations in a fuel cell test bench, this allows to asses the performance of the scheme as well as the difficulties that arise in real applications.