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Article | Open Access

Research on Fuzzy-Proportional-Integral-Derivative Control Strategy Improved by Artificial Bee Colony algorithm for Thermal Management of Hybrid Fuel Cell

Wei Dong1Xuqing Feng2Taoxiang Mei2Xiang Li2Zhenzong He2,3( )
COMAC Beijing Aircraft Technology Research Institute, Beijing, China
College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Key Laboratory of Thermal Management and Energy Utilization of Aircraft, Ministry of Industry and Information Technology, Nanjing, China
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Abstract

The proton exchange membrane fuel cell (PEMFC) and the hydrogen hybrid power system are studied by the fuzzy-PID (FPID) control method and the fuzzy-PID control method by Artificial Bee Colony algorithm (ABC-FPID), respectively. The results reveal that compared with the FPID control method, the temperature overshoot of the PEMFC stack under the ABC-FPID control method is decreased by 0.6%. Moreover, the circulating water flow rate within the full operating envelope (about 3 min) is reduced by 19.46 L, which means the ABC-FPID control method is more effective in regulating the stack temperature. Then, the ABC-FPID control method is proposed to study the hydrogen hybrid power system, and the system output power matching, operating characteristic curve of the fuel cell, state of charge (SOC) of the lithium battery, system efficiency and hydrogen demand are obtained. The results indicate that the maximum system efficiency reaches 46.3%, the average system efficiency is 33.8%, and the average hydrogen demand is 0.192 kg/s. Overall, the ABC-FPID control method can efficiently ensure the stability of the fuel cell’s output power, and actively prompt the lithium battery to fulfill the function of “peak shaving and valley filling” under variable load power conditions.

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Frontiers in Heat and Mass Transfer
Article number: 4

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Cite this article:
Dong W, Feng X, Mei T, et al. Research on Fuzzy-Proportional-Integral-Derivative Control Strategy Improved by Artificial Bee Colony algorithm for Thermal Management of Hybrid Fuel Cell. Frontiers in Heat and Mass Transfer, 2026, 24(1): 4. https://doi.org/10.32604/fhmt.2026.075846

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Received: 10 November 2025
Accepted: 20 January 2026
Published: 28 February 2026
© The Author 2026.

This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.