Fused multi-model predictive control with adaptive compensation for proton exchange membrane fuel cell air supply system

Regulating the air supply is crucial for high efficiency and reliable operation of proton exchange membrane fuel cell systems (PEMFCs). In this study, a fused multi-model predictive control (FM-MPC) with an adaptive compensation is proposed for the oxygen excess ratio (OER) regulation of the air supply system. The FM-MPC is designed based on the linearized PEMFC model at low and high power phases, with two linear MPCs imple-mented and combined using adaptive featured weights. An adaptive compensation strategy is created to address the imbalance of the two MPCs and external load disturbances. The stability of the proposed control is analyzed using Lyapunov's second law. Simulation results demonstrate that the proposed method exhibits less overshoot and faster response than conventional MPCs, with the OER total sum-of-squares error (TSSE) reduced by 59.4% and 87.7% for New European Driving Cycle (NEDC) and Urban Dynamometer Driving Schedule (UDDS) con-ditions, respectively. Finally, a Hardware-In-the-Loop (HIL) experiment verifies the real-time application po-tential of the proposed controller, with a mean relative error (MRE) of 1.12% between experiment and simulation.

Automated summary

A fused multi-model predictive control (FM-MPC) with adaptive compensation is proposed for regulating the oxygen excess ratio (OER) in air supply systems. The FM-MPC is designed based on a linearized PEMFC model and combines two linear MPCs with adaptive featured weights. An adaptive compensation strategy is used to address imbalances and external load disturbances. Simulation results show that the proposed method outperforms conventional MPCs with reduced OER total sum-of-squares error (TSSE) by 59.4% and 87.7% for NEDC and UDDS conditions respectively. HIL experiments verify the real-time application potential with a mean relative error (MRE) of 1.12%.