To address the strong coupling between stack inlet airflow and cathode supply pressure, along with the optimization control problem of a Proton Exchange Membrane Fuel Cell (PEMFC) system, this paper proposes a hierarchical control scheme comprising an optimization layer and a control layer for a 100 kW vehicular PEMFC air supply subsystem. A high-fidelity model characterizing the cathode-side dynamic mass transfer process is first established based on experimental data. The air compressor is modeled using a data-driven approach, while the electrochemical parameters in the semi-empirical voltage model are identified via a hybrid Simulated Annealing-Particle Swarm Optimization (SA-PSO) algorithm. For the optimization layer, a two-dimensional objective function describing system efficiency is developed, and the Multi-strategy Enhanced Dung Beetle Optimization (MEDBO) is designed to obtain flow and pressure references that maximize efficiency under varying current densities. Optimization results show that MEDBO improves system efficiency by 0.6%–5.2% over calibration experiments, significantly outperforming the standard DBO algorithm. For the control layer, an Inverted Decoupling (ID)-based Active Disturbance Rejection Control (ID-ADRC) strategy is proposed for flow-pressure decoupling. Simulation results demonstrate that ID-ADRC achieves superior decoupling performance over Proportional Integral Differential (PID) and ID-PID, limiting coupling-induced fluctuations in airflow and pressure to 2.4 g/s and 0.94 kPa, respectively, while exhibiting stronger robustness against external disturbances. In addition, the China Light-duty Vehicle Test Cycle-Passenger car (CLTC-P) driving condition further validated the effective decoupling performance, with the absolute errors of airflow and pressure control maintained within 4.2 g/s and 3 kPa, respectively. These findings offer new insights into the control and optimization of air supply management for vehicular PEMFC systems.
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Wei et al. (2026) studied this question.
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