Adaptive control for robust air flow management in an automotive fuel cell system

Surge control in a centrifugal air compressor is crucial to ensure the reliable operation of a fuel cell system, but few studies have reported on compressor surges in fuel cell systems. This study presents an effective surge control algorithm with a surge predictive compressor model under various operating conditions of an automotive fuel cell system. Unlike previous studies on the air management systems of an automotive fuel cell, this study presents an analytic compressor model which is a nonlinear dynamic model with surge prediction capability. In this study, a model reference adaptive control (MRAC) is introduced, to avoid compressor surge during the dynamic operation of a fuel cell system. The adaptive control was compared with the nominal feedback control in the air management system of an automotive fuel cell operating within normal conditions, under transient and steady-state responses. Also, when a surge was detected in the system, the adaptive control algorithm was fast enough to recover the air mass flow rate to normal ranges. Based on these results, it can be concluded that the MRAC algorithm shows better performance than the nominal feedback control algorithm with respect to the transient behaviors and surge recovery of an automotive fuel cell system.