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Multi-objective decoupling control of thermal management system for PEM fuel cell

  • Jun Hong Chen
  • , Pu He
  • , Ze Hong He
  • , Jia Le Song
  • , Xian Hao Liu
  • , Yun Tian Xiao
  • , Ming Yang Wang
  • , Lu Zheng Yang
  • , Yu Tong Mu
  • , Wen Quan Tao
  • Xi'an Jiaotong University

科研成果: 期刊稿件文章同行评审

20 引用 (Scopus)

摘要

Operating temperature is an important factor that affects the efficiency, durability, and safety of proton exchange membrane fuel cells (PEMFC). Thus, a thermal management system is necessary for controlling the appropriate temperature. In this paper, a novel thermal management system based on two-stage utilization of cooling air is first established, whose core characteristic is utilizing the temperature difference between the cooling air leaving the main radiator and the auxiliary radiator. The novel thermal management system can reduce the parasitic power of the fan by 59.27 % and improve the temperature control effect to a certain extent. The traditional feedforward decoupling control based on system identification is first adopted to control the temperature and surpasses dual-PID on all the 5 indexes, which are Integral Absolute Error Criterion (IAE) of temperature difference, IAE of inlet coolant temperature, parasitic power of fan, average overshoot of temperature difference and average overshoot of inlet coolant temperature. The multi-objective decoupling control based on multi-objective optimization is then proposed to further improve the temperature control effect on the basis of traditional feedforward decoupling control. The above 5 indexes are chosen as the optimization objectives, the decoupling coefficients are chosen as the decision variables, and the Pareto set is obtained by NSGAⅡ and NSGAⅢ. The results show that the proposed multi-objective decoupling control has the main advantages as follows: (1) It can provide comprehensive optimization options for different design preferences; (2) It can significantly optimize a certain objective while other objectives are not too extreme; (3) It has the ability to surpass traditional feedforward decoupling control on all the 5 indexes; (4) It does not rely on the system identification.

源语言英语
期刊论文编号100447
期刊Energy and AI
18
DOI
出版状态已出版 - 12月 2024

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