Optimal oxygen excess ratio tracking of proton exchange membrane fuel cell with uncertainty based on robust model predictive control strategy

Abstract

AbstractTo address the challenge of tracking the optimal oxygen excess ratio (OER) in the cell stack cathode of the proton exchange membrane fuel cell (PEMFC), which is subject to norm‐bounded parameter uncertainty and frequent external perturbations, this manuscript provides a novel robust model predictive control strategy with a state feedback control structure and hard constraints. We aim to minimize the tracking error of OER while maximizing the net power under varying operational conditions of the PEMFC. Initially, a control‐oriented model for the air supply system is built and its accuracy is validated by comparing it with experimental results. Next, we construct the discrete state‐space equations for optimal control and employ the linear matrix inequality (LMI) method to transform the problem of difficult min‐max optimization solutions into a convex optimization problem with LMI constraints. Finally, the effectiveness of the proposed control algorithm is validated through simulation. The results demonstrate the strong robustness and superiority of the proposed controller against uncertainties in plant parameters for robust OER trajectory tracking. It improves the transient performance through robust precision tracking applications, which will eventually accelerate PEMFC commercialization.