IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i14p5193-d865139.html
   My bibliography  Save this article

The Characterization of the Electric Double-Layer Capacitor (EDLC) Using Python/MATLAB/Simulink (PMS)-Hybrid Model

Author

Listed:
  • Chrispin Tumba Tshiani

    (Department of Electrical Engineering, School of Engineering, College of Science, Engineering and Technology (CSET), Florida Campus, University of South Africa, Johannesburg 1709, South Africa)

  • Patrice Umenne

    (Department of Electrical Engineering, School of Engineering, College of Science, Engineering and Technology (CSET), Florida Campus, University of South Africa, Johannesburg 1709, South Africa)

Abstract

This paper investigates the characterization of an electric double-layer capacitor (EDLC). In this study, the 300 F and 400 F EDLC supercapacitors are connected in a circuit in a laboratory experiment to produce their charge/discharge profiles at a constant current. The acquired charge/discharge profiles were used to determine the mathematical parameters of the EDLCs using the “Faranda model”, or “two-branch model”, of the EDLC. The parameters extracted from the equivalent circuit model were then used as inputs to a designed Python/MATLAB/Simulink (PMS)-hybrid model of an EDLC. This was simulated to obtain charge/discharge profiles. The resulting experimental- and simulated-charge/discharge profiles of the EDLCs were compared with each other, by superimposing their profiles to determine the accuracy of the PMS model. The PMS model was found to be very accurate. The innovation of this work lies in modeling a supercapacitor, mostly in the Python programming language in combination with a MATLAB/Simulink model. The experimental-charge/discharge profiles obtained were used to calculate the equivalent circuit resistance (ESR) and the capacitance of the EDLCs, which were compared with the existing datasheet values of the EDLCs. The characterization of the EDLC supercapacitor was done to derive a flexible PMS model of the EDLC, which can be used in a microgrid hybrid energy-storage system (HESS) to show the potential of the EDLC in improving battery lifespan.

Suggested Citation

  • Chrispin Tumba Tshiani & Patrice Umenne, 2022. "The Characterization of the Electric Double-Layer Capacitor (EDLC) Using Python/MATLAB/Simulink (PMS)-Hybrid Model," Energies, MDPI, vol. 15(14), pages 1-14, July.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:5193-:d:865139
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/14/5193/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/14/5193/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sekhar Raghu Raman & Ka-Wai (Eric) Cheng & Xiang-Dang Xue & Yat-Chi Fong & Simon Cheung, 2021. "Hybrid Energy Storage System with Vehicle Body Integrated Super-Capacitor and Li-Ion Battery: Model, Design and Implementation, for Distributed Energy Storage," Energies, MDPI, vol. 14(20), pages 1-22, October.
    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. Chrispin Tumba Tshiani & Patrice Umenne, 2022. "The Impact of the Electric Double-Layer Capacitor (EDLC) in Reducing Stress and Improving Battery Lifespan in a Hybrid Energy Storage System (HESS) System," Energies, MDPI, vol. 15(22), pages 1-19, November.

    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. Vishnu P. Sidharthan & Yashwant Kashyap & Panagiotis Kosmopoulos, 2023. "Adaptive-Energy-Sharing-Based Energy Management Strategy of Hybrid Sources in Electric Vehicles," Energies, MDPI, vol. 16(3), pages 1-26, January.
    2. Yuriy Bilan & Marcin Rabe & Katarzyna Widera, 2022. "Distributed Energy Resources: Operational Benefits," Energies, MDPI, vol. 15(23), pages 1-7, November.
    3. Zhangyu Lu & Xizheng Zhang, 2022. "Composite Non-Linear Control of Hybrid Energy-Storage System in Electric Vehicle," Energies, MDPI, vol. 15(4), pages 1-15, February.
    4. Khaled Itani & Alexandre De Bernardinis, 2022. "Electrothermal Multicriteria Comparative Analysis of Two Competitive Powertrains Applied to a Two Front Wheel Driven Electric Vehicle during Extreme Regenerative Braking Operations," Energies, MDPI, vol. 15(22), pages 1-27, November.

    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:15:y:2022:i:14:p:5193-:d:865139. 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.