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author:

Zhang, Zhi (Zhang, Zhi.) [1] | Shen, Yunde (Shen, Yunde.) [2] | Ou, Kai (Ou, Kai.) [3] | Liu, Zhuwei (Liu, Zhuwei.) [4] | Xuan, Dongji (Xuan, Dongji.) [5]

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Abstract:

The operational performance of proton exchange membrane fuel cells (PEMFC) is highly influenced by temperature, making effective thermal management essential. However, the multivariate coupling between pumps and radiators presents significant control challenges. To address this issue, a dual DDPG-PID control strategy is proposed, integrating temperature and flow rate variations to enhance system stability and response. Simulation results demonstrate that the proposed method significantly reduces temperature control errors and improves response time compared to conventional PID-based strategies. Specifically, the D-DDPG PID achieves a temperature error reduction of up to 75.4% and shortens the average tuning time by up to 25.6% compared to PSO-PID. Furthermore, the strategy optimizes cooling system performance, demonstrating its effectiveness in PEMFC thermal management. © 2025 by the authors.

Keyword:

Cooling systems Deep learning Gradient methods Proportional control systems Proton exchange membrane fuel cells (PEMFC) System stability Three term control systems

Community:

  • [ 1 ] [Zhang, Zhi]College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou; 325035, China
  • [ 2 ] [Shen, Yunde]College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou; 325035, China
  • [ 3 ] [Ou, Kai]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 4 ] [Liu, Zhuwei]College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou; 325035, China
  • [ 5 ] [Xuan, Dongji]College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou; 325035, China

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Source :

Hydrogen (Switzerland)

Year: 2025

Issue: 2

Volume: 6

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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