@inproceedings{342a50a81e53484990596ede24d99b82,
title = "Optimization of Fuel Cell Air Supply System Based on Particle Swarm Optimization",
abstract = "Focusing on the maximum power point tracking for fuel cell systems (FCSs), this paper proposes the optimization of the fuel cell (FC) air supply systems based on the particle swarm optimization (PSO) algorithm. An air compressor and stack models were built based on the working mechanism, and the model's accuracy was verified through experimental data. Aiming at the maximum output power of the FCS, a PSO algorithm was designed to obtain the air supply system's working air mass flow and pressure. The power of the FCS was optimized at different current density points. Compared with the single optimized air mass flow and conventional fixed value methods, the system power increased by an average of 630 W and 380 W in self-defined operating conditions.",
keywords = "air supply system, fuel cell system, particle swarm optimization, power optimization",
author = "Jinzhou Chen and Hongwen He and Shengwei Quan and Zhendong Zhang and Ruoyan Han",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 China Automation Congress, CAC 2023 ; Conference date: 17-11-2023 Through 19-11-2023",
year = "2023",
doi = "10.1109/CAC59555.2023.10451594",
language = "English",
series = "Proceedings - 2023 China Automation Congress, CAC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2265--2269",
booktitle = "Proceedings - 2023 China Automation Congress, CAC 2023",
address = "United States",
}