Nonlinear MPC for Fuel Cell Air Path Control with Experimental Validation

Abstract

Fuel cell systems are a viable alternative for energy conversion in stationary and mobile applications. Advanced control algorithms are the main levers to ensure safe operation in transients and increase the applicability of fuel cell systems in research and industry. This paper focuses on the control of the fuel cell air path and the net power output for a small-scale fuel cell system. For safe operation and durability even in transients, tight bounds on stoichiometry and compressor operation must be ensured at all times. To tackle this challenge, a data-based nonlinear model predictive controller is implemented and experimentally validated on a cathode path test bench with a real-time fuel cell stack simulation. Our results show accurate tracking, safe operation, and a reduction in settling time to new power reference set points of approximately 50% compared to a reference controller.