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author:

Chen, Jinzhou (Chen, Jinzhou.) [1] | He, Hongwen (He, Hongwen.) [2] | Quan, Shengwei (Quan, Shengwei.) [3] | Wei, Zhongbao (Wei, Zhongbao.) [4] | Zhang, Zhendong (Zhang, Zhendong.) [5] | Wang, Ya-Xiong (Wang, Ya-Xiong.) [6]

Indexed by:

EI

Abstract:

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). © 2023

Keyword:

Altitude control Centrifugal compressors Centrifugation Fuel cells Fuel systems Gas compressors Particle swarm optimization (PSO)

Community:

  • [ 1 ] [Chen, Jinzhou]National Engineering Research Centre of Electric Vehicles, Beijing Institute of Technology, Beijing; 100081, China
  • [ 2 ] [He, Hongwen]National Engineering Research Centre of Electric Vehicles, Beijing Institute of Technology, Beijing; 100081, China
  • [ 3 ] [He, Hongwen]Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing; 314019, China
  • [ 4 ] [Quan, Shengwei]National Engineering Research Centre of Electric Vehicles, Beijing Institute of Technology, Beijing; 100081, China
  • [ 5 ] [Wei, Zhongbao]National Engineering Research Centre of Electric Vehicles, Beijing Institute of Technology, Beijing; 100081, China
  • [ 6 ] [Zhang, Zhendong]National Engineering Research Centre of Electric Vehicles, Beijing Institute of Technology, Beijing; 100081, China
  • [ 7 ] [Wang, Ya-Xiong]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China

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Source :

Fuel

ISSN: 0016-2361

Year: 2024

Volume: 356

6 . 7 0 0

JCR@2023

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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