Study of nonlinear control schemes for an automotive traction PEM fuel cell system

Abstract

To be practical in automotive traction applications, fuel cell systems must provide power output levels of performance that rival that of typical internal combustion engines. In so doing, transient behavior is one of the keys for success of fuel cell systems in vehicles. The focus of this paper is on the air/fuel supply subsystem in tracking an optimum variable pressurization and air flow for maximum system efficiency during load transients. The control-oriented model developed for this study considers electrochemistry, thermodynamics, and fluid flow principles for a 13-state, nonlinear model of a pressurized fuel cell system. For control purposes, a model reduction is performed, and several multi-variable control designs are examined. The first technique uses an observer-based linear optimum control which combines a feed-forward approach based on the steady-state plant inverse response, coupled to a multi-variable LQR feedback control. An extension of that approach, for control in the full nonlinear range of operation, leads to the second technique, nonlinear gain-scheduled control. Some enhancements were applied to overcome the fast variations in the scheduling variable. Finally, a rule-based, output feedback control, implemented with fuzzy logic, is coupled with a nonlinear feed-forward approach, and is examined under the same conditions applied to the first two techniques. The control designs developed are compared in simulation studies to investigate robustness to disturbance, time delay, and actuator limitations.