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Time-Domain Circuit Modelling for Hybrid Supercapacitors

Author

Listed:
  • Fabio Corti

    (Dipartimento di Ingegneria, Università di Perugia, Via G. Duranti 67, 06125 Perugia, Italy)

  • Michelangelo-Santo Gulino

    (Dipartimento di Ingegneria Industriale, Università di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy)

  • Maurizio Laschi

    (Dipartimento di Ingegneria Industriale, Università di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy)

  • Gabriele Maria Lozito

    (Dipartimento di Ingegneria dell’Informazione, Università di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy)

  • Luca Pugi

    (Dipartimento di Ingegneria Industriale, Università di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy)

  • Alberto Reatti

    (Dipartimento di Ingegneria dell’Informazione, Università di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy)

  • Dario Vangi

    (Dipartimento di Ingegneria Industriale, Università di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy)

Abstract

Classic circuit modeling for supercapacitors is limited in representing the strongly non-linear behavior of the hybrid supercapacitor technology. In this work, two novel modeling techniques suitable to represent the time-domain electrical behavior of a hybrid supercapacitor are presented. The first technique enhances a well-affirmed circuit model by introducing specific non-linearities. The second technique models the device through a black-box approach with a neural network. Both the modeling techniques are validated experimentally using a workbench to acquire data from a real hybrid supercapacitor. The proposed models, suitable for different supercapacitor technologies, achieve higher accuracy and generalization capabilities compared to those already presented in the literature. Both modeling techniques allow for an accurate representation of both short-time domain and steady-state simulations, providing a valuable asset in electrical designs featuring supercapacitors.

Suggested Citation

  • Fabio Corti & Michelangelo-Santo Gulino & Maurizio Laschi & Gabriele Maria Lozito & Luca Pugi & Alberto Reatti & Dario Vangi, 2021. "Time-Domain Circuit Modelling for Hybrid Supercapacitors," Energies, MDPI, vol. 14(20), pages 1-16, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:20:p:6837-:d:659745
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    References listed on IDEAS

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    1. Gustavo Navarro & Jorge Nájera & Jorge Torres & Marcos Blanco & Miguel Santos & Marcos Lafoz, 2020. "Development and Experimental Validation of a Supercapacitor Frequency Domain Model for Industrial Energy Applications Considering Dynamic Behaviour at High Frequencies," Energies, MDPI, vol. 13(5), pages 1-18, March.
    2. Oussama Ouramdane & Elhoussin Elbouchikhi & Yassine Amirat & Ehsan Sedgh Gooya, 2021. "Optimal Sizing and Energy Management of Microgrids with Vehicle-to-Grid Technology: A Critical Review and Future Trends," Energies, MDPI, vol. 14(14), pages 1-45, July.
    3. Henry Miniguano & Andrés Barrado & Cristina Fernández & Pablo Zumel & Antonio Lázaro, 2019. "A General Parameter Identification Procedure Used for the Comparative Study of Supercapacitors Models," Energies, MDPI, vol. 12(9), pages 1-20, May.
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    Cited by:

    1. Giacomo Talluri & Gabriele Maria Lozito & Francesco Grasso & Carlos Iturrino Garcia & Antonio Luchetta, 2021. "Optimal Battery Energy Storage System Scheduling within Renewable Energy Communities," Energies, MDPI, vol. 14(24), pages 1-23, December.
    2. Kasun Subasinghage & Kosala Gunawardane & Nisitha Padmawansa & Nihal Kularatna & Mehdi Moradian, 2022. "Modern Supercapacitors Technologies and Their Applicability in Mature Electrical Engineering Applications," Energies, MDPI, vol. 15(20), pages 1-15, October.
    3. Alejandro Rojano-Padrón & Marc Olivier Metais & Francisco J. Ramos-Real & Yannick Perez, 2023. "Tenerife’s Infrastructure Plan for Electromobility: A MATSim Evaluation," Energies, MDPI, vol. 16(3), pages 1-24, January.

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