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Modeling and control of PEMFC air supply system based on T-S fuzzy theory and predictive control

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  • Yang, Duo
  • Pan, Rui
  • Wang, Yujie
  • Chen, Zonghai

Abstract

The proton exchange membrane fuel cell has become the most widely used fuel cell in fuel cell vehicles. An effective and accurate control approach for its air supply system is crucial to ensure the performance and safety of the fuel cell system. In order to ensure safe and efficient operation of the air supply, this paper provides a novel modeling and control method based on Takagi-Sugeno fuzzy theory and predictive control. A local controlled autoregressive integrated moving average model for the air flow control is put forward, then the control-oriented T-S model is designed based on multi-model scheduling. The controller architecture is based on a fuzzy generalized predictive controller. The proposed controller can control the oxygen excess ratio in the ideal range and effectively suppress the fluctuation caused by the load change. In addition, an optimal control strategy is proposed aiming at avoiding the oxygen starvation and maximizing the system net power. According to the control results, the proposed method is proved to be able to accurately control the air supply at desire values. It enhances system output performance by fast response to better support the vehicle load variation, and improving the net power and system energy efficiency.

Suggested Citation

  • Yang, Duo & Pan, Rui & Wang, Yujie & Chen, Zonghai, 2019. "Modeling and control of PEMFC air supply system based on T-S fuzzy theory and predictive control," Energy, Elsevier, vol. 188(C).
  • Handle: RePEc:eee:energy:v:188:y:2019:i:c:s0360544219317736
    DOI: 10.1016/j.energy.2019.116078
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    References listed on IDEAS

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    Cited by:

    1. Peng Yin & Jinzhou Chen & Hongwen He, 2023. "Control of Oxygen Excess Ratio for a PEMFC Air Supply System by Intelligent PID Methods," Sustainability, MDPI, vol. 15(11), pages 1-20, May.
    2. Hu, Haowen & Ou, Kai & Yuan, Wei-Wei, 2023. "Fused multi-model predictive control with adaptive compensation for proton exchange membrane fuel cell air supply system," Energy, Elsevier, vol. 284(C).
    3. Zhang, Caizhi & Zhang, Yuqi & Wang, Lei & Deng, Xiaozhi & Liu, Yang & Zhang, Jiujun, 2023. "A health management review of proton exchange membrane fuel cell for electric vehicles: Failure mechanisms, diagnosis techniques and mitigation measures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    4. Deng, Zhihua & Chen, Qihong & Zhang, Liyan & Zhou, Keliang & Zong, Yi & Fu, Zhichao & Liu, Hao, 2021. "Data-driven reconstruction of interpretable model for air supply system of proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 299(C).
    5. Zhang, Qinguo & Tong, Zheming & Tong, Shuiguang & Cheng, Zhewu, 2021. "Modeling and dynamic performance research on proton exchange membrane fuel cell system with hydrogen cycle and dead-ended anode," Energy, Elsevier, vol. 218(C).
    6. Liu, Zhao & Chen, Huicui & Peng, Lian & Ye, Xichen & Xu, Sichen & Zhang, Tong, 2022. "Feedforward-decoupled closed-loop fuzzy proportion-integral-derivative control of air supply system of proton exchange membrane fuel cell," Energy, Elsevier, vol. 240(C).
    7. Vu, Hoang Nghia & Truong Le Tri, Dat & Nguyen, Huu Linh & Kim, Younghyeon & Yu, Sangseok, 2023. "Multifunctional bypass valve for water management and surge protection in a proton-exchange membrane fuel cell supply-air system," Energy, Elsevier, vol. 278(C).
    8. Wan, Xin & Luo, Xiong-Lin, 2020. "Economic optimization of chemical processes based on zone predictive control with redundancy variables," Energy, Elsevier, vol. 212(C).
    9. Chen, Huicui & Liu, Zhao & Ye, Xichen & Yi, Liu & Xu, Sichen & Zhang, Tong, 2022. "Air flow and pressure optimization for air supply in proton exchange membrane fuel cell system," Energy, Elsevier, vol. 238(PC).

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