This study demonstrates the applicability of an explicit model predictive controller (ExMPC) to the air mass flow control in a fuel cell electric vehicle. The two control tasks comprise the supply of air to the fuel cell stack for the electrochemical reaction as well as the dilution of hydrogen in the outlet gas flow of the cathode subsystem. With the aim of achieving zero control deviation for steady states, the linear model in the state observer is extended with two perturbations. During the experimental validation of the proposed controller, fast dynamics are achieved with the ExMPC, which generally exploits the limits of the control variables. After the calibration of the ExMPC, the final comparison to a set of reference PI controllers reveals a significant improvement in the closed-loop behavior of the cathode subsystem during step changes in the controller setpoints.
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This study demonstrates the applicability of an explicit model predictive controller (ExMPC) to the air mass flow control in a fuel cell electric vehicle. The two control tasks comprise the supply of air to the fuel cell stack for the electrochemical reaction as well as the dilution of hydrogen in the outlet gas flow of the cathode subsystem. With the aim of achieving zero control deviation for steady states, the linear model in the state observer is extended with two perturbations. During the e...
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