IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v237y2024ipcs0960148124018408.html
   My bibliography  Save this article

RBFNN based fixed time sliding mode control for PEMFC air supply system with input delay

Author

Listed:
  • Derakhshannia, Mehran
  • Moosapour, Seyyed Sajjad

Abstract

Ensuring rapid regulation of the oxygen excess ratio (OER) in proton exchange membrane fuel cells (PEMFC) during load changes is an important challenge. In this paper, fixed time sliding mode control of a PEMFC with input delay has been investigated. First, a simplified fourth-order nonlinear dynamical model with input disturbance and input delay is considered and a cascade structure is selected for the control design. A radial basis function neural network (RBFNN) is designed to estimate the input disturbance. To achieve precise estimation, a Cuckoo Search Algorithm is utilized to calculate the parameters of the RBFNN. Then, a new sliding mode controller is proposed for trajectory tracking within a fixed time. To ensure the effectiveness of the proposed controller, the fixed time convergence of both sliding and reaching phases is investigated and proven. Finally, a robust prediction based sliding mode control is designed for the PEMFC system that by incorporating the disturbance estimation, can eliminate the effect of input delay. The effectiveness and robustness of the proposed controller are validated via comparative simulations. It is noteworthy that this is the first study to propose predictor based control for input delay PEMFCs.

Suggested Citation

  • Derakhshannia, Mehran & Moosapour, Seyyed Sajjad, 2024. "RBFNN based fixed time sliding mode control for PEMFC air supply system with input delay," Renewable Energy, Elsevier, vol. 237(PC).
    • Handle: RePEc:eee:renene:v:237:y:2024:i:pc:s0960148124018408
    DOI: 10.1016/j.renene.2024.121772
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124018408
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2024.121772?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mohammed Yousri Silaa & Mohamed Derbeli & Oscar Barambones & Ali Cheknane, 2020. "Design and Implementation of High Order Sliding Mode Control for PEMFC Power System," Energies, MDPI, vol. 13(17), pages 1-15, August.
    2. Su, Hang & Ye, Donghao & Cai, Yuanqi & Guo, Wei, 2022. "Air starvation of proton exchange membrane fuel cells and its beneficial effects on performance," Applied Energy, Elsevier, vol. 323(C).
    3. Zhang, Hong & Yuan, Tiejiang, 2022. "Optimization and economic evaluation of a PEM electrolysis system considering its degradation in variable-power operations," Applied Energy, Elsevier, vol. 324(C).
    4. 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).
    5. 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).
    6. Javaid, Usman & Mehmood, Adeel & Iqbal, Jamshed & Uppal, Ali Arshad, 2023. "Neural network and URED observer based fast terminal integral sliding mode control for energy efficient polymer electrolyte membrane fuel cell used in vehicular technologies," Energy, Elsevier, vol. 269(C).
    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. 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).
    2. Antonio Nicolò Mancino & Carla Menale & Francesco Vellucci & Manlio Pasquali & Roberto Bubbico, 2023. "PEM Fuel Cell Applications in Road Transport," Energies, MDPI, vol. 16(17), pages 1-27, August.
    3. Mohamed Derbeli & Asma Charaabi & Oscar Barambones & Cristian Napole, 2021. "High-Performance Tracking for Proton Exchange Membrane Fuel Cell System PEMFC Using Model Predictive Control," Mathematics, MDPI, vol. 9(11), pages 1-17, May.
    4. Behzadi, Amirmohammad & Duwig, Christophe & Ploskic, Adnan & Holmberg, Sture & Sadrizadeh, Sasan, 2024. "Application to novel smart techniques for decarbonization of commercial building heating and cooling through optimal energy management," Applied Energy, Elsevier, vol. 376(PA).
    5. Pawel Latosinski & Andrzej Bartoszewicz, 2023. "Sliding Mode Controllers in Energy Systems and Other Applications," Energies, MDPI, vol. 16(3), pages 1-4, January.
    6. Quan, Shengwei & Wang, Ya-Xiong & Xiao, Xuelian & He, Hongwen & Sun, Fengchun, 2021. "Feedback linearization-based MIMO model predictive control with defined pseudo-reference for hydrogen regulation of automotive fuel cells," Applied Energy, Elsevier, vol. 293(C).
    7. Lopez-Juarez, M. & Rockstroh, T. & Novella, R. & Vijayagopal, R., 2024. "A methodology to develop multi-physics dynamic fuel cell system models validated with vehicle realistic drive cycle data," Applied Energy, Elsevier, vol. 358(C).
    8. Giuseppe Corda & Antonio Cucurachi & Stefano Fontanesi & Alessandro d’Adamo, 2023. "Three-Dimensional CFD Simulation of a Proton Exchange Membrane Electrolysis Cell," Energies, MDPI, vol. 16(16), pages 1-17, August.
    9. Khlid Ben Hamad & Doudou N. Luta & Atanda K. Raji, 2021. "A Grid-Tied Fuel Cell Multilevel Inverter with Low Harmonic Distortions," Energies, MDPI, vol. 14(3), pages 1-24, January.
    10. Arias, Ignacio & Battisti, Felipe G. & Romero-Ramos, J.A. & Pérez, Manuel & Valenzuela, Loreto & Cardemil, José & Escobar, Rodrigo, 2024. "Assessing system-level synergies between photovoltaic and proton exchange membrane electrolyzers for solar-powered hydrogen production," Applied Energy, Elsevier, vol. 368(C).
    11. Muhammad Majid Gulzar, 2023. "Maximum Power Point Tracking of a Grid Connected PV Based Fuel Cell System Using Optimal Control Technique," Sustainability, MDPI, vol. 15(5), pages 1-18, February.
    12. Zhang, Yuqi & Li, Yu & Zhang, Caizhi & Yang, Yunzi & Yu, Xingzi & Niu, Tong & Wang, Lei & Wang, Gucheng, 2024. "Intelligent diagnosis of proton exchange membrane fuel cell water states based on flooding-specificity experiment and deep learning method," Renewable Energy, Elsevier, vol. 222(C).
    13. Hassan Ali, Hossam & Fathy, Ahmed, 2024. "Reliable exponential distribution optimizer-based methodology for modeling proton exchange membrane fuel cells at different conditions," Energy, Elsevier, vol. 292(C).
    14. 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).
    15. María Villarreal Vives, Ana & Wang, Ruiqi & Roy, Sumit & Smallbone, Andrew, 2023. "Techno-economic analysis of large-scale green hydrogen production and storage," Applied Energy, Elsevier, vol. 346(C).
    16. Xia, Zhifeng & Chen, Huicui & Li, Weihong & Zhang, Ruirui & Xu, Yiming & Zhang, Tong & Pei, Pucheng, 2024. "Characterization and analysis of current distribution for oxygen starvation diagnosis: A research based on segmented PEMFC technology," Renewable Energy, Elsevier, vol. 237(PC).
    17. Wang, Mingkai & Pei, Pucheng & Xu, Yiming & Ren, Peng & Wang, He, 2024. "Novel methods for fault diagnosis and enhancing CO tolerance in PEM fuel cells fueled with impure hydrogen," Applied Energy, Elsevier, vol. 375(C).
    18. Wang, Renkang & Li, Kai & Cao, Jishen & Yang, Haiyu & Tang, Hao, 2024. "Air supply subsystem efficiency optimization for fuel cell power system with layered control method," Renewable Energy, Elsevier, vol. 235(C).
    19. Fu, Jianqin & Wang, Huailin & Sun, Xilei & Bao, Huanhuan & Wang, Xun & Liu, Jingping, 2024. "Multi-objective optimization for impeller structure parameters of fuel cell air compressor using linear-based boosting model and reference vector guided evolutionary algorithm," Applied Energy, Elsevier, vol. 363(C).
    20. Qian, Zhang & Hongwei, Wang & Chunlei, Liu & Yi, An, 2024. "Establishment and identification of MIMO fractional Hammerstein model with colored noise for PEMFC system," Chaos, Solitons & Fractals, Elsevier, vol. 180(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:eee:renene:v:237:y:2024:i:pc:s0960148124018408. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.