Differential flatness-based observer design for a PEM fuel cell using adaptive-gain sliding mode differentiators

In this paper, we propose a differential flatness-based observer for a PEM fuel cell air-feed system. The proposed observer uses the measurements of supply manifold air pressure and compressor mass flow rate in order to estimate the oxygen partial pressure, nitrogen partial pressure and the compressor speed. An adaptive-gain Second Order Sliding Mode differentiator based on super-twisting algorithm is designed to estimate the time derivatives of the system outputs when the boundary of higher time derivative is unknown. Then, the states are estimated based on these values. The objective is to minimize the number of embedded sensors in order to get a precise and economic solution. The feasibility and effectiveness of the proposed approach is demonstrated through simulation results obtained from a nonlinear fuel cell system.