IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i19p6140-d643966.html
   My bibliography  Save this article

An Improved Fuzzy PID Control Method Considering Hydrogen Fuel Cell Voltage-Output Characteristics for a Hydrogen Vehicle Power System

Author

Listed:
  • Zili Wang

    (State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China)

  • Guodong Yi

    (State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China)

  • Shaoju Zhang

    (State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China)

Abstract

The hydrogen fuel cell (HFC) vehicle is an important clean energy vehicle which has prospects for development. The behavior of the hydrogen fuel cell (HFC) vehicle power system, and in particular, the proton-exchange membrane fuel cell, has been extensively studied as of recent. The development of the dynamic system modeling technology is of paramount importance for HFC vehicle studies; however, it is hampered by the separation of the electrochemical properties and dynamic properties. In addition, the established model matching the follow-up control method lacks applicability. In attempts to counter these obstructions, we proposed an improved fuzzy (Proportional Integral Derivative) PID control method considering HFC voltage-output characteristics. By developing both the electrochemical and dynamic model for HFC vehicle, we can realize the coordinated control of HFC and power cell. The simulation results are in good agreement with the experimental results in the two models. The proposed control algorithm has a good control effect in all stages of HFC vehicle operation.

Suggested Citation

  • Zili Wang & Guodong Yi & Shaoju Zhang, 2021. "An Improved Fuzzy PID Control Method Considering Hydrogen Fuel Cell Voltage-Output Characteristics for a Hydrogen Vehicle Power System," Energies, MDPI, vol. 14(19), pages 1-18, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6140-:d:643966
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/19/6140/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/19/6140/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrzej Szałek & Ireneusz Pielecha & Wojciech Cieslik, 2021. "Fuel Cell Electric Vehicle (FCEV) Energy Flow Analysis in Real Driving Conditions (RDC)," Energies, MDPI, vol. 14(16), pages 1-17, August.
    2. Andrea Pietra & Marco Gianni & Nicola Zuliani & Stefano Malabotti & Rodolfo Taccani, 2021. "Experimental Characterization of an Alkaline Electrolyser and a Compression System for Hydrogen Production and Storage," Energies, MDPI, vol. 14(17), pages 1-17, August.
    3. Sutharssan, Thamo & Montalvao, Diogo & Chen, Yong Kang & Wang, Wen-Chung & Pisac, Claudia & Elemara, Hakim, 2017. "A review on prognostics and health monitoring of proton exchange membrane fuel cell," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 440-450.
    4. Daniel Ritzberger & Christoph Hametner & Stefan Jakubek, 2020. "A Real-Time Dynamic Fuel Cell System Simulation for Model-Based Diagnostics and Control: Validation on Real Driving Data," Energies, MDPI, vol. 13(12), pages 1-20, June.
    5. Abdin, Z. & Webb, C.J. & Gray, E.MacA., 2016. "PEM fuel cell model and simulation in Matlab–Simulink based on physical parameters," Energy, Elsevier, vol. 116(P1), pages 1131-1144.
    6. Chavan, Sudarshan L. & Talange, Dhananjay B., 2017. "Modeling and performance evaluation of PEM fuel cell by controlling its input parameters," Energy, Elsevier, vol. 138(C), pages 437-445.
    7. Chen, Kui & Laghrouche, Salah & Djerdir, Abdesslem, 2019. "Degradation model of proton exchange membrane fuel cell based on a novel hybrid method," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    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. Chen, Kui & Badji, Abderrezak & Laghrouche, Salah & Djerdir, Abdesslem, 2022. "Polymer electrolyte membrane fuel cells degradation prediction using multi-kernel relevance vector regression and whale optimization algorithm," Applied Energy, Elsevier, vol. 318(C).
    2. Zhao, Jian & Ozden, Adnan & Shahgaldi, Samaneh & Alaefour, Ibrahim E. & Li, Xianguo & Hamdullahpur, Feridun, 2018. "Effect of Pt loading and catalyst type on the pore structure of porous electrodes in polymer electrolyte membrane (PEM) fuel cells," Energy, Elsevier, vol. 150(C), pages 69-76.
    3. 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).
    4. El-Hay, E.A. & El-Hameed, M.A. & El-Fergany, A.A., 2019. "Optimized Parameters of SOFC for steady state and transient simulations using interior search algorithm," Energy, Elsevier, vol. 166(C), pages 451-461.
    5. Zou, Wei & Froning, Dieter & Shi, Yan & Lehnert, Werner, 2021. "An online adaptive model for the nonlinear dynamics of fuel cell voltage," Applied Energy, Elsevier, vol. 288(C).
    6. Atyabi, Seyed Ali & Afshari, Ebrahim & Wongwises, Somchai & Yan, Wen-Mon & Hadjadj, Abdellah & Shadloo, Mostafa Safdari, 2019. "Effects of assembly pressure on PEM fuel cell performance by taking into accounts electrical and thermal contact resistances," Energy, Elsevier, vol. 179(C), pages 490-501.
    7. Mingzhang Pan & Chengjie Pan & Jinyang Liao & Chao Li & Rong Huang & Qiwei Wang, 2021. "Assessment of Sensitivity to Evaluate the Impact of Operating Parameters on Stability and Performance in Proton Exchange Membrane Fuel Cells," Energies, MDPI, vol. 14(14), pages 1-23, July.
    8. Deng, Zhihua & Chan, Siew Hwa & Chen, Qihong & Liu, Hao & Zhang, Liyan & Zhou, Keliang & Tong, Sirui & Fu, Zhichao, 2023. "Efficient degradation prediction of PEMFCs using ELM-AE based on fuzzy extension broad learning system," Applied Energy, Elsevier, vol. 331(C).
    9. Samuel Simon Araya & Fan Zhou & Simon Lennart Sahlin & Sobi Thomas & Christian Jeppesen & Søren Knudsen Kær, 2019. "Fault Characterization of a Proton Exchange Membrane Fuel Cell Stack," Energies, MDPI, vol. 12(1), pages 1-17, January.
    10. Abel Rubio & Wilton Agila & Leandro González & Jonathan Aviles-Cedeno, 2023. "Distributed Intelligence in Autonomous PEM Fuel Cell Control," Energies, MDPI, vol. 16(12), pages 1-25, June.
    11. Basem E. Elnaghi & M. N. Abelwhab & Ahmed M. Ismaiel & Reham H. Mohammed, 2023. "Solar Hydrogen Variable Speed Control of Induction Motor Based on Chaotic Billiards Optimization Technique," Energies, MDPI, vol. 16(3), pages 1-33, January.
    12. Xuexia Zhang & Zixuan Yu & Weirong Chen, 2019. "Life Prediction Based on D-S ELM for PEMFC," Energies, MDPI, vol. 12(19), pages 1-15, September.
    13. Martin Vrlić & Daniel Ritzberger & Stefan Jakubek, 2020. "Safe and Efficient Polymer Electrolyte Membrane Fuel Cell Control Using Successive Linearization Based Model Predictive Control Validated on Real Vehicle Data," Energies, MDPI, vol. 13(20), pages 1-16, October.
    14. Katarzyna Turoń, 2022. "Multi-Criteria Decision Analysis during Selection of Vehicles for Car-Sharing Services—Regular Users’ Expectations," Energies, MDPI, vol. 15(19), pages 1-15, October.
    15. Pei, Pucheng & Meng, Yining & Chen, Dongfang & Ren, Peng & Wang, Mingkai & Wang, Xizhong, 2023. "Lifetime prediction method of proton exchange membrane fuel cells based on current degradation law," Energy, Elsevier, vol. 265(C).
    16. Xu, Shuhui & Wang, Yong & Wang, Zhi, 2019. "Parameter estimation of proton exchange membrane fuel cells using eagle strategy based on JAYA algorithm and Nelder-Mead simplex method," Energy, Elsevier, vol. 173(C), pages 457-467.
    17. Li, Haolong & Chen, Qihong & Zhang, Liyan & Liu, Li & Xiao, Peng, 2023. "Degradation prediction of proton exchange membrane fuel cell based on the multi-inputs Bi-directional long short-term memory," Applied Energy, Elsevier, vol. 344(C).
    18. Matthieu Matignon & Toufik Azib & Mehdi Mcharek & Ahmed Chaibet & Adriano Ceschia, 2023. "Real-Time Integrated Energy Management Strategy Applied to Fuel Cell Hybrid Systems," Energies, MDPI, vol. 16(6), pages 1-21, March.
    19. Chen, Dongfang & Pei, Pucheng & Meng, Yining & Ren, Peng & Li, Yuehua & Wang, Mingkai & Wang, Xizhong, 2022. "Novel extraction method of working condition spectrum for the lifetime prediction and energy management strategy evaluation of automotive fuel cells," Energy, Elsevier, vol. 255(C).
    20. Ke Li & Heng Zhang & Xiaoyu Zheng & Chang Liu & Qianding Chen, 2022. "Hydrogen Production by Water Electrolysis with Low Power and High Efficiency Based on Pre-Magnetic Polarization," Energies, MDPI, vol. 15(5), pages 1-12, March.

    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:14:y:2021:i:19:p:6140-:d:643966. 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.