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Real-time power optimization based on PSO feedforward and perturbation & observation of fuel cell system for high altitude.

Authors :
Chen, Jinzhou
He, Hongwen
Quan, Shengwei
Wei, Zhongbao
Zhang, Zhendong
Wang, Ya-Xiong
Source :
Fuel. Jan2024, Vol. 356, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

• The working characteristics of compressors at different altitudes are established. • A real-time power optimization strategy based on the P&O algorithm was designed. • PSO feedforward-based P&O method is developed to adjust the air compressor voltage. • Results verify the advantages of the proposed strategy under variable altitude conditions. The control technology of the air supply system is key to the performance and reliability of the fuel cell system (FCS). However, due to the low oxygen pressure in high altitude environment, the power consumption of the air compressor is large, and the output power of FCS is seriously degraded. To effectively increase the output power of the FCS under changeable altitude conditions, this article introduces a real-time power optimization strategy based on the particle swarm optimization (PSO) feedforward and perturbation and observation (P&O) algorithm. Considering the change of total entropy and loss of centrifugal air compressor with altitude, the working characteristics of centrifugal compressors at different altitudes are studied. Aiming at the long optimization time of the traditional P&O method and the misjudgment problem when the external conditions change drastically, the PSO feedforward-based P&O method is designed to adjust the air compressor voltage. The results show that the proposed strategy has real-time power optimization capability and can adapt to altitude change. The average setting time is 1.8 s when the operating condition changes and the power decreases to 9.1% at 3000 m altitude under a higher load (300 A). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00162361
Volume :
356
Database :
Academic Search Index
Journal :
Fuel
Publication Type :
Academic Journal
Accession number :
173343233
Full Text :
https://doi.org/10.1016/j.fuel.2023.129551