IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i17p6207-d898286.html
   My bibliography  Save this article

Thévenin’s Battery Model Parameter Estimation Based on Simulink

Author

Listed:
  • Giulio Barletta

    (Department of Energy (DENERG), Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Turin, Italy)

  • Piera DiPrima

    (Energy Center, Politecnico di Torino, Via P. Borsellino 38/18, 10129 Turin, Italy
    Department of Applied Science and Technology (DISAT), Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Turin, Italy)

  • Davide Papurello

    (Department of Energy (DENERG), Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Turin, Italy
    Energy Center, Politecnico di Torino, Via P. Borsellino 38/18, 10129 Turin, Italy)

Abstract

Lithium-ion batteries (LIB) proved over time to be one of the best choices among rechargeable batteries. Their small size, high energy density, long life, and low maintenance need make them a prominent candidate for the role of the most widespread energy storage system. They have the potential to monopolize the green technology sector. An accurate definition of the parameters defining the behaviour of the battery in different operating conditions is thus essential, as their knowledge proves crucial in certain fields such as those that involve electric vehicles. This paper proposes the estimation of the values of the parameters of the Thévenin equivalent circuit of a LIB commercial cell. Experimental data obtained through constant current charge/discharge cycles are analysed through a Simulink model, and results are obtained as a function of the state of charge (SOC) for a fixed and controlled temperature value. The results achieved with the proposed model can monitor the salient parameters of the equivalent circuit with an error between 7 and 10%.

Suggested Citation

  • Giulio Barletta & Piera DiPrima & Davide Papurello, 2022. "Thévenin’s Battery Model Parameter Estimation Based on Simulink," Energies, MDPI, vol. 15(17), pages 1-10, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6207-:d:898286
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/17/6207/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/17/6207/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ding, Xiaofeng & Zhang, Donghuai & Cheng, Jiawei & Wang, Binbin & Luk, Patrick Chi Kwong, 2019. "An improved Thevenin model of lithium-ion battery with high accuracy for electric vehicles," Applied Energy, Elsevier, vol. 254(C).
    2. Zerrahn, Alexander & Schill, Wolf-Peter & Kemfert, Claudia, 2018. "On the economics of electrical storage for variable renewable energy sources," European Economic Review, Elsevier, vol. 108(C), pages 259-279.
    3. Kebede, Abraham Alem & Kalogiannis, Theodoros & Van Mierlo, Joeri & Berecibar, Maitane, 2022. "A comprehensive review of stationary energy storage devices for large scale renewable energy sources grid integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    4. Alexandros Nikolian & Yousef Firouz & Rahul Gopalakrishnan & Jean-Marc Timmermans & Noshin Omar & Peter Van den Bossche & Joeri Van Mierlo, 2016. "Lithium Ion Batteries—Development of Advanced Electrical Equivalent Circuit Models for Nickel Manganese Cobalt Lithium-Ion," Energies, MDPI, vol. 9(5), pages 1-23, May.
    5. Jaguemont, J. & Boulon, L. & Dubé, Y., 2016. "A comprehensive review of lithium-ion batteries used in hybrid and electric vehicles at cold temperatures," Applied Energy, Elsevier, vol. 164(C), pages 99-114.
    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. Wang, Bin & Wang, Shifeng & Tang, Yuanyuan & Tsang, Chi-Wing & Dai, Jinchuan & Leung, Michael K.H. & Lu, Xiao-Ying, 2019. "Micro/nanostructured MnCo2O4.5 anodes with high reversible capacity and excellent rate capability for next generation lithium-ion batteries," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    2. Gerbaulet, Clemens & von Hirschhausen, Christian & Kemfert, Claudia & Lorenz, Casimir & Oei, Pao-Yu, 2019. "European electricity sector decarbonization under different levels of foresight," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 141, pages 973-987.
    3. Behrang Shirizadeh, Quentin Perrier, and Philippe Quirion, 2022. "How Sensitive are Optimal Fully Renewable Power Systems to Technology Cost Uncertainty?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    4. Das, Himadry Shekhar & Tan, Chee Wei & Yatim, A.H.M., 2017. "Fuel cell hybrid electric vehicles: A review on power conditioning units and topologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 268-291.
    5. Mehmet C. Yagci & Thomas Feldmann & Elmar Bollin & Michael Schmidt & Wolfgang G. Bessler, 2022. "Aging Characteristics of Stationary Lithium-Ion Battery Systems with Serial and Parallel Cell Configurations," Energies, MDPI, vol. 15(11), pages 1-19, May.
    6. Li, Yi & Liu, Kailong & Foley, Aoife M. & Zülke, Alana & Berecibar, Maitane & Nanini-Maury, Elise & Van Mierlo, Joeri & Hoster, Harry E., 2019. "Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    7. Helm, Carsten & Mier, Mathias, 2021. "Steering the energy transition in a world of intermittent electricity supply: Optimal subsidies and taxes for renewables and storage," Journal of Environmental Economics and Management, Elsevier, vol. 109(C).
    8. Motoaki, Yutaka & Yi, Wenqi & Salisbury, Shawn, 2018. "Empirical analysis of electric vehicle fast charging under cold temperatures," Energy Policy, Elsevier, vol. 122(C), pages 162-168.
    9. Ragab El-Sehiemy & Mohamed A. Hamida & Ehab Elattar & Abdullah Shaheen & Ahmed Ginidi, 2022. "Nonlinear Dynamic Model for Parameter Estimation of Li-Ion Batteries Using Supply–Demand Algorithm," Energies, MDPI, vol. 15(13), pages 1-20, June.
    10. Jan Abrell & Sebastian Rausch & Clemens Streitberger, 2022. "The Economic and Climate Value of Flexibility in Green Energy Markets," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(2), pages 289-312, October.
    11. Qin, Yudi & Du, Jiuyu & Lu, Languang & Gao, Ming & Haase, Frank & Li, Jianqiu & Ouyang, Minggao, 2020. "A rapid lithium-ion battery heating method based on bidirectional pulsed current: Heating effect and impact on battery life," Applied Energy, Elsevier, vol. 280(C).
    12. Xuliang Tang & Heng Wan & Weiwen Wang & Mengxu Gu & Linfeng Wang & Linfeng Gan, 2023. "Lithium-Ion Battery Remaining Useful Life Prediction Based on Hybrid Model," Sustainability, MDPI, vol. 15(7), pages 1-18, April.
    13. Schauf, Magnus & Schwenen, Sebastian, 2023. "System price dynamics for battery storage," Energy Policy, Elsevier, vol. 183(C).
    14. Li, Yong & Wang, Liye & Feng, Yanbiao & Liao, Chenglin & Yang, Jue, 2024. "An online state-of-health estimation method for lithium-ion battery based on linear parameter-varying modeling framework," Energy, Elsevier, vol. 298(C).
    15. Sun, Xilei & Fu, Jianqin, 2024. "Many-objective optimization of BEV design parameters based on gradient boosting decision tree models and the NSGA-III algorithm considering the ambient temperature," Energy, Elsevier, vol. 288(C).
    16. Auguadra, Marco & Ribó-Pérez, David & Gómez-Navarro, Tomás, 2023. "Planning the deployment of energy storage systems to integrate high shares of renewables: The Spain case study," Energy, Elsevier, vol. 264(C).
    17. Calise, Francesco & Cappiello, Francesco Liberato & Cimmino, Luca & Dentice d’Accadia, Massimo & Vicidomini, Maria, 2023. "Renewable smart energy network: A thermoeconomic comparison between conventional lithium-ion batteries and reversible solid oxide fuel cells," Renewable Energy, Elsevier, vol. 214(C), pages 74-95.
    18. Tao, Laifa & Cheng, Yujie & Lu, Chen & Su, Yuzhuan & Chong, Jin & Jin, Haizu & Lin, Yongshou & Noktehdan, Azadeh, 2017. "Lithium-ion battery capacity fading dynamics modelling for formulation optimization: A stochastic approach to accelerate the design process," Applied Energy, Elsevier, vol. 202(C), pages 138-152.
    19. Xingxing Wang & Peilin Ye & Shengren Liu & Yu Zhu & Yelin Deng & Yinnan Yuan & Hongjun Ni, 2023. "Research Progress of Battery Life Prediction Methods Based on Physical Model," Energies, MDPI, vol. 16(9), pages 1-20, April.
    20. Wiese, Frauke & Schlecht, Ingmar & Bunke, Wolf-Dieter & Gerbaulet, Clemens & Hirth, Lion & Jahn, Martin & Kunz, Friedrich & Lorenz, Casimir & Mühlenpfordt, Jonathan & Reimann, Juliane & Schill, Wolf-P, 2019. "Open Power System Data – Frictionless data for electricity system modelling," Applied Energy, Elsevier, vol. 236(C), pages 401-409.

    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:17:p:6207-:d:898286. 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.