IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i11p8500-d1154147.html
   My bibliography  Save this article

Control of Oxygen Excess Ratio for a PEMFC Air Supply System by Intelligent PID Methods

Author

Listed:
  • Peng Yin

    (National Engineering Research Centre of Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Jinzhou Chen

    (National Engineering Research Centre of Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Hongwen He

    (National Engineering Research Centre of Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

Abstract

The hydrogen fuel cell is a quite promising green device, which could be applied in extensive fields. However, as a complex nonlinear system involving a number of subsystems, the fuel cell system requires multiple variables to be effectively controlled. Oxygen excess ratio (OER) is the key indicator to be controlled to avoid oxygen starvation, which may result in severe performance degradation and life shortage of the fuel cell stack. In this paper, a nonlinear air supply system model integrated with the fuel cell stack voltage model is first built, based on physical laws and empirical data; then, conventional proportional-integral-derivative (PID) controls for the oxygen excess ratio are implemented. On this basis, fuzzy logic inference and neural network algorithm are integrated into the conventional PID controller to tune the gain coefficients, respectively. The simulation results verify that the fuzzy PID controller with seven subsets could clearly improve the dynamic responses of the fuel cells in both constant and variable OER controls, with small overshoots and the fastest settling times of less than 0.2 s.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:8500-:d:1154147
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/11/8500/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/11/8500/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jia, Chunchun & Zhou, Jiaming & He, Hongwen & Li, Jianwei & Wei, Zhongbao & Li, Kunang & Shi, Man, 2023. "A novel energy management strategy for hybrid electric bus with fuel cell health and battery thermal- and health-constrained awareness," Energy, Elsevier, vol. 271(C).
    2. Jiaming Zhou & Chunxiao Feng & Qingqing Su & Shangfeng Jiang & Zhixian Fan & Jiageng Ruan & Shikai Sun & Leli Hu, 2022. "The Multi-Objective Optimization of Powertrain Design and Energy Management Strategy for Fuel Cell–Battery Electric Vehicle," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
    3. Liu, Ze & Zhang, Baitao & Xu, Sichuan, 2022. "Research on air mass flow-pressure combined control and dynamic performance of fuel cell system for vehicles application," Applied Energy, Elsevier, vol. 309(C).
    4. Zeng, Tao & Xiao, Long & Chen, Jinrui & Li, Yu & Yang, Yi & Huang, Shulong & Deng, Chenghao & Zhang, Caizhi, 2023. "Feedforward-based decoupling control of air supply for vehicular fuel cell system: Methodology and experimental validation," Applied Energy, Elsevier, vol. 335(C).
    5. 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).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mohammed Yousri Silaa & Oscar Barambones & José Antonio Cortajarena & Patxi Alkorta & Aissa Bencherif, 2023. "PEMFC Current Control Using a Novel Compound Controller Enhanced by the Black Widow Algorithm: A Comprehensive Simulation Study," Sustainability, MDPI, vol. 15(18), pages 1-23, September.
    2. Xu Liang & Huifang Kang & Rui Zeng & Yue Pang & Yun Yang & Yunlu Qiu & Yuanxu Tao & Jun Shen, 2024. "Impact of the Structural Parameters on the Performance of a Regenerative-Type Hydrogen Recirculation Blower for Vehicular Proton Exchange Membrane Fuel Cells," Sustainability, MDPI, vol. 16(5), pages 1-28, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kun He & Dongchen Qin & Jiangyi Chen & Tingting Wang & Hongxia Wu & Peizhuo Wang, 2023. "Adaptive Equivalent Consumption Minimization Strategy for Fuel Cell Buses Based on Driving Style Recognition," Sustainability, MDPI, vol. 15(10), pages 1-17, May.
    2. 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).
    3. Zhiming Zhang & Alexander Rex & Jiaming Zhou & Xinfeng Zhang & Gangqiang Huang & Jinming Zhang & Tong Zhang, 2023. "Dynamic Simulation Model and Experimental Validation of One Passive Fuel Cell–Battery Hybrid Powertrain for an Electric Light Scooter," Sustainability, MDPI, vol. 15(17), pages 1-19, September.
    4. Sanghyun Yun & Jinwon Yun & Jaeyoung Han, 2023. "Development of a 470-Horsepower Fuel Cell–Battery Hybrid Xcient Dynamic Model Using Simscape TM," Energies, MDPI, vol. 16(24), pages 1-22, December.
    5. Imed Khabbouchi & Dhaou Said & Aziz Oukaira & Idir Mellal & Lyes Khoukhi, 2023. "Machine Learning and Game-Theoretic Model for Advanced Wind Energy Management Protocol (AWEMP)," Energies, MDPI, vol. 16(5), pages 1-15, February.
    6. Wan, Xin & Luo, Xiong-Lin, 2020. "Economic optimization of chemical processes based on zone predictive control with redundancy variables," Energy, Elsevier, vol. 212(C).
    7. Jia, Chunchun & He, Hongwen & Zhou, Jiaming & Li, Jianwei & Wei, Zhongbao & Li, Kunang, 2023. "A novel health-aware deep reinforcement learning energy management for fuel cell bus incorporating offline high-quality experience," Energy, Elsevier, vol. 282(C).
    8. Shangzhe Yu & Dominik Schäfer & Shidong Zhang & Roland Peters & Felix Kunz & Rüdiger-A. Eichel, 2023. "A Three-Dimensional Time-Dependent Model of the Degradation Caused by Chromium Poisoning in a Solid Oxide Fuel Cell Stack," Energies, MDPI, vol. 16(23), pages 1-23, November.
    9. 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).
    10. Zhiming Zhang & Sai Wu & Huimin Miao & Tong Zhang, 2022. "Numerical Investigation of Flow Channel Design and Tapered Slope Effects on PEM Fuel Cell Performance," Sustainability, MDPI, vol. 14(18), pages 1-15, September.
    11. Wang, Yichun & Zhang, Yuanzhi & Zhang, Caizhi & Zhou, Jiaming & Hu, Donghai & Yi, Fengyan & Fan, Zhixian & Zeng, Tao, 2023. "Genetic algorithm-based fuzzy optimization of energy management strategy for fuel cell vehicles considering driving cycles recognition," Energy, Elsevier, vol. 263(PF).
    12. Mojgan Fayyazi & Paramjotsingh Sardar & Sumit Infent Thomas & Roonak Daghigh & Ali Jamali & Thomas Esch & Hans Kemper & Reza Langari & Hamid Khayyam, 2023. "Artificial Intelligence/Machine Learning in Energy Management Systems, Control, and Optimization of Hydrogen Fuel Cell Vehicles," Sustainability, MDPI, vol. 15(6), pages 1-38, March.
    13. Liviu I. Scurtu & Ioan Szabo & Marius Gheres, 2023. "Numerical Analysis of Crashworthiness on Electric Vehicle’s Battery Case with Auxetic Structure," Energies, MDPI, vol. 16(15), pages 1-18, August.
    14. Lu, Dagang & Yi, Fengyan & Hu, Donghai & Li, Jianwei & Yang, Qingqing & Wang, Jing, 2023. "Online optimization of energy management strategy for FCV control parameters considering dual power source lifespan decay synergy," Applied Energy, Elsevier, vol. 348(C).
    15. Zeng, Tao & Xiao, Long & Chen, Jinrui & Li, Yu & Yang, Yi & Huang, Shulong & Deng, Chenghao & Zhang, Caizhi, 2023. "Feedforward-based decoupling control of air supply for vehicular fuel cell system: Methodology and experimental validation," Applied Energy, Elsevier, vol. 335(C).
    16. 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).
    17. Kunang Li & Chunchun Jia & Xuefeng Han & Hongwen He, 2023. "A Novel Minimal-Cost Power Allocation Strategy for Fuel Cell Hybrid Buses Based on Deep Reinforcement Learning Algorithms," Sustainability, MDPI, vol. 15(10), pages 1-15, May.
    18. Marek Guzek & Jerzy Jackowski & Rafał S. Jurecki & Emilia M. Szumska & Piotr Zdanowicz & Marcin Żmuda, 2024. "Electric Vehicles—An Overview of Current Issues—Part 1—Environmental Impact, Source of Energy, Recycling, and Second Life of Battery," Energies, MDPI, vol. 17(1), pages 1-25, January.
    19. Han, Jie & Liu, Wenxue & Zheng, Yusheng & Khalatbarisoltani, Arash & Yang, Yalian & Hu, Xiaosong, 2023. "Health-conscious predictive energy management strategy with hybrid speed predictor for plug-in hybrid electric vehicles: Investigating the impact of battery electro-thermal-aging models," Applied Energy, Elsevier, vol. 352(C).
    20. Hongqing Chu & Zongxuan Li & Jialin Wang & Jinlong Hong, 2023. "Fuel-Saving-Oriented Collaborative Driving Strategy for Commercial Vehicles Based on Driving Style Recognition," Energies, MDPI, vol. 16(17), pages 1-21, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:8500-:d:1154147. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.