TY - JOUR
T1 - Coordinated Optimization Control Strategy for Air Supply System in Proton Exchange Membrane Fuel Cells
AU - Zhang, Silong
AU - Sun, Hengkai
AU - Chen, Jicheng
AU - Zhang, Hui
AU - Zhao, Lidong
N1 - Publisher Copyright:
© 1982-2012 IEEE.
PY - 2026
Y1 - 2026
N2 - The dynamic behavior of the air supply system critically influences overall fuel cell performance and efficiency. However, strong coupling and intrinsic nonlinearities in the cathode pose significant challenges for control design, while inherent compressor characteristics may induce pressure-flow mismatches and increase the risk of surge during abrupt load variations. Existing control strategies relying on precise physical modeling often struggle to capture parameter variations and model uncertainties, and commonly neglect surge suppression. To address these challenges, this study proposes a coordinated optimization control strategy for the air supply system. Specifically, a data-driven feedforward controller with feasible domain constraints is developed based on an air subsystem experiment, and a particle swarm optimization-optimized super-twisting sliding mode controller is integrated to ensure high-precision tracking. The proposed control framework is validated through combined simulations and experiments, demonstrating improved tracking performance, efficiency, and surge resilience.
AB - The dynamic behavior of the air supply system critically influences overall fuel cell performance and efficiency. However, strong coupling and intrinsic nonlinearities in the cathode pose significant challenges for control design, while inherent compressor characteristics may induce pressure-flow mismatches and increase the risk of surge during abrupt load variations. Existing control strategies relying on precise physical modeling often struggle to capture parameter variations and model uncertainties, and commonly neglect surge suppression. To address these challenges, this study proposes a coordinated optimization control strategy for the air supply system. Specifically, a data-driven feedforward controller with feasible domain constraints is developed based on an air subsystem experiment, and a particle swarm optimization-optimized super-twisting sliding mode controller is integrated to ensure high-precision tracking. The proposed control framework is validated through combined simulations and experiments, demonstrating improved tracking performance, efficiency, and surge resilience.
KW - Air supply
KW - decoupling control
KW - proton exchange membrane fuel cell (PEMFC)
KW - super-twisting sliding mode controller (STSMC)
UR - https://www.scopus.com/pages/publications/105038693589
U2 - 10.1109/TIE.2026.3677661
DO - 10.1109/TIE.2026.3677661
M3 - 文章
AN - SCOPUS:105038693589
SN - 0278-0046
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
ER -