Nonlinear Model Predictive Control of a PEM Fuel Cell System for Cathode Exhaust Gas Generation
نویسندگان
چکیده
Polymer electrolyte membrane (PEM) fuel cells are highly efficient energy converters and provide electrical energy, cathode exhaust gas with low oxygen concentration and water. They are investigated as replacement for auxiliary power units (APU) that are currently used for electrical power generation on aircraft. For generation of oxygen depleted cathode exhaust air (ODA) oxygen concentration must be 10-11%. A challenging task is controlling the fuel cell system for this product and simultaneously keeping fuel cell stack degradation, voltage losses and stack damage as low as possible as well as keeping the system within operational limitations such as bounds and gradients on control parameters. This constrained control task for PEM fuel cell systems is attacked by a nonlinear model predictive control (NMPC) strategy. Simulation and experimental results are shown.
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Modeling, state estimation and nonlinear model predictive control of cathode exhaust gas mass flow for PEM fuel cells
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