IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2022i1p228-d1014609.html
   My bibliography  Save this article

Cascade Control Method of Sliding Mode and PID for PEMFC Air Supply System

Author

Listed:
  • Aihua Tang

    (School of Vehicle Engineering, Chongqing University of Technology, Chongqing 400054, China)

  • Lin Yang

    (School of Vehicle Engineering, Chongqing University of Technology, Chongqing 400054, China)

  • Tao Zeng

    (School of Electrical Engineering, Chongqing University, Chongqing 400044, China
    Chongqing Changan New Energy Vehicle Technology Co., Ltd., Chongqing 400023, China)

  • Quanqing Yu

    (School of Automotive Engineering, Harbin Institute of Technology, Weihai 264209, China)

Abstract

Proton exchange membrane fuel cells (PEMFC) are vulnerable to oxygen starvation when working under variable load. To address these issues, a cascade control strategy of sliding mode control (SMC) and Proportion Integration Differentiation (PID) control is proposed in this study. The goal of the control strategy is to enhance the PEMFC’s net power by adjusting the oxygen excess ratio (OER) to the reference value in the occurrence of a load change. In order to estimate the cathode pressure and reconstruct the OER, an expansion state observer (ESO) is developed. The study found that there is a maximum error of about 2200Pa between the estimated cathode pressure and the actual pressure. Then the tracking of the actual OER to the reference OER is realized by the SMC and PID cascade control. The simulation study, which compared the control performance of several methods—including PID controller, adaptive fuzzy PID controller and the proposed controller, i.e., the SMC and PID cascade controller—was carried out under various load-changing scenarios. The outcomes demonstrate that the proposed SMC and PID cascade controller method really does have a faster response time. The overshoot is reduced by approximately 3.4% compared to PID control and by about 0.09% compared to fuzzy adaptive PID. SMC and PID cascade control reference OER performs more effectively in terms of tracking compared to PID control and adaptive fuzzy PID control.

Suggested Citation

  • Aihua Tang & Lin Yang & Tao Zeng & Quanqing Yu, 2022. "Cascade Control Method of Sliding Mode and PID for PEMFC Air Supply System," Energies, MDPI, vol. 16(1), pages 1-13, December.
  • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:228-:d:1014609
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/1/228/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/1/228/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Matraji, Imad & Laghrouche, Salah & Jemei, Samir & Wack, Maxime, 2013. "Robust control of the PEM fuel cell air-feed system via sub-optimal second order sliding mode," Applied Energy, Elsevier, vol. 104(C), pages 945-957.
    2. Daud, W.R.W. & Rosli, R.E. & Majlan, E.H. & Hamid, S.A.A. & Mohamed, R. & Husaini, T., 2017. "PEM fuel cell system control: A review," Renewable Energy, Elsevier, vol. 113(C), pages 620-638.
    3. Feng, Yanbiao & Dong, Zuomin, 2020. "Integrated design and control optimization of fuel cell hybrid mining truck with minimized lifecycle cost," Applied Energy, Elsevier, vol. 270(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. Antoine Bäumler & Jianwen Meng & Abdelmoudjib Benterki & Toufik Azib & Moussa Boukhnifer, 2023. "A System-Level Modeling of PEMFC Considering Degradation Aspect towards a Diagnosis Process," Energies, MDPI, vol. 16(14), pages 1-19, July.

    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. Bizon, Nicu, 2019. "Real-time optimization strategies of Fuel Cell Hybrid Power Systems based on Load-following control: A new strategy, and a comparative study of topologies and fuel economy obtained," Applied Energy, Elsevier, vol. 241(C), pages 444-460.
    2. Hou, Junbo & Yang, Min & Ke, Changchun & Zhang, Junliang, 2020. "Control logics and strategies for air supply in PEM fuel cell engines," Applied Energy, Elsevier, vol. 269(C).
    3. Bizon, Nicu, 2019. "Fuel saving strategy using real-time switching of the fueling regulators in the proton exchange membrane fuel cell system," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    4. Li, Yuehua & Pei, Pucheng & Ma, Ze & Ren, Peng & Huang, Hao, 2020. "Analysis of air compression, progress of compressor and control for optimal energy efficiency in proton exchange membrane fuel cell," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    5. Nicu Bizon & Mihai Oproescu, 2018. "Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control," Energies, MDPI, vol. 11(12), pages 1-32, December.
    6. Nicu Bizon & Phatiphat Thounthong, 2021. "A Simple and Safe Strategy for Improving the Fuel Economy of a Fuel Cell Vehicle," Mathematics, MDPI, vol. 9(6), pages 1-29, March.
    7. Komova, O.V. & Simagina, V.I. & Butenko, V.R. & Odegova, G.V. & Bulavchenko, O.A. & Nikolaeva, O.A. & Ozerova, A.M. & Lipatnikova, I.L. & Tayban, E.S. & Mukha, S.A. & Netskina, O.V., 2022. "Dehydrogenation of ammonia borane recrystallized by different techniques," Renewable Energy, Elsevier, vol. 184(C), pages 460-472.
    8. Martin Vrlić & Daniel Ritzberger & Stefan Jakubek, 2021. "Model-Predictive-Control-Based Reference Governor for Fuel Cells in Automotive Application Compared with Performance from a Real Vehicle," Energies, MDPI, vol. 14(8), pages 1-17, April.
    9. Barzegari, Mohammad M. & Dardel, Morteza & Alizadeh, Ebrahim & Ramiar, Abas, 2016. "Dynamic modeling and validation studies of dead-end cascade H2/O2 PEM fuel cell stack with integrated humidifier and separator," Applied Energy, Elsevier, vol. 177(C), pages 298-308.
    10. Wu, Kangcheng & Du, Qing & Zu, Bingfeng & Wang, Yupeng & Cai, Jun & Gu, Xin & Xuan, Jin & Jiao, Kui, 2021. "Enabling real-time optimization of dynamic processes of proton exchange membrane fuel cell: Data-driven approach with semi-recurrent sliding window method," Applied Energy, Elsevier, vol. 303(C).
    11. Bizon, Nicu, 2019. "Efficient fuel economy strategies for the Fuel Cell Hybrid Power Systems under variable renewable/load power profile," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    12. 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.
    13. Van Du Phan & Hoai-An Trinh & Kyoung Kwan Ahn, 2023. "Finite-Time Command Filtered Control for Oxygen-Excess Ratio of Proton Exchange Membrane Fuel Cell Systems with Prescribed Performance," Mathematics, MDPI, vol. 11(4), pages 1-17, February.
    14. Nicu Bizon & Mircea Raceanu & Emmanouel Koudoumas & Adriana Marinoiu & Emmanuel Karapidakis & Elena Carcadea, 2020. "Renewable/Fuel Cell Hybrid Power System Operation Using Two Search Controllers of the Optimal Power Needed on the DC Bus," Energies, MDPI, vol. 13(22), pages 1-26, November.
    15. Luo, Lizhong & Jian, Qifei & Huang, Bi & Huang, Zipeng & Zhao, Jing & Cao, Songyang, 2019. "Experimental study on temperature characteristics of an air-cooled proton exchange membrane fuel cell stack," Renewable Energy, Elsevier, vol. 143(C), pages 1067-1078.
    16. Elkholy, M.H. & Metwally, Hamid & Farahat, M.A. & Senjyu, Tomonobu & Elsayed Lotfy, Mohammed, 2022. "Smart centralized energy management system for autonomous microgrid using FPGA," Applied Energy, Elsevier, vol. 317(C).
    17. Tomislav Capuder & Bojana Barać & Matija Kostelac & Matej Krpan, 2023. "Three-Stage Modeling Framework for Analyzing Islanding Capabilities of Decarbonized Energy Communities," Energies, MDPI, vol. 16(11), pages 1-24, May.
    18. Xun, Qian & Murgovski, Nikolce & Liu, Yujing, 2022. "Chance-constrained robust co-design optimization for fuel cell hybrid electric trucks," Applied Energy, Elsevier, vol. 320(C).
    19. Won, Jinyeon & Oh, Hwanyeong & Hong, Jongsup & Kim, Minjin & Lee, Won-Yong & Choi, Yoon-Young & Han, Soo-Bin, 2021. "Hybrid diagnosis method for initial faults of air supply systems in proton exchange membrane fuel cells," Renewable Energy, Elsevier, vol. 180(C), pages 343-352.
    20. Zou, Wei & Froning, Dieter & Shi, Yan & Lehnert, Werner, 2021. "Working zone for a least-squares support vector machine for modeling polymer electrolyte fuel cell voltage," Applied Energy, Elsevier, vol. 283(C).

    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:jeners:v:16:y:2022:i:1:p:228-:d:1014609. 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.