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Calculating Available Charge and Energy of Lithium-Ion Cells Based on OCV and Internal Resistance

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  • Fabian Steger

    (CARISSMA Institute of Electric, Connected, and Secure Mobility, Technische Hochschule Ingolstadt, 85049 Ingolstadt, Germany
    School of Engineering, Royal Melbourne Institute of Technology, 124 La Trobe Street, Melbourne, VIC 3000, Australia
    Department of IT & Technology, IU Internationale Hochschule, Juri-Gagarin-Ring 152, 99084 Erfurt, Germany)

  • Jonathan Krogh

    (Department of Mechanical and Electrical Engineering, University of Southern Denmark, Campusvej 55, 5220 Odense, Denmark)

  • Lasantha Meegahapola

    (School of Engineering, Royal Melbourne Institute of Technology, 124 La Trobe Street, Melbourne, VIC 3000, Australia)

  • Hans-Georg Schweiger

    (CARISSMA Institute of Electric, Connected, and Secure Mobility, Technische Hochschule Ingolstadt, 85049 Ingolstadt, Germany)

Abstract

The design and operation of performant and safe electric vehicles depend on precise knowledge of the behavior of their electrochemical energy storage systems. The performance of the battery management systems often relies on the discrete-time battery models, which can correctly emulate the battery characteristics. Among the available methods, electric circuit-based equations have shown to be especially useful in describing the electrical characteristics of batteries. To overcome the existing drawbacks, such as discrete-time simulations for parameter estimation and the usage of look-up tables, a set of equations has been developed in this study that solely relies on the open-circuit voltage and the internal resistance of a battery. The parameters can be obtained from typical cell datasheets or can be easily extracted via standard measurements. The proposed equations allow for the direct analytical determination of available discharge capacity and the available energy content depending on the discharge current, as well as the Peukert exponent. The fidelity of the proposed system was validated experimentally using 18650 NMC and LFP lithium-ion cells, and the results are in close agreement with the datasheet.

Suggested Citation

  • Fabian Steger & Jonathan Krogh & Lasantha Meegahapola & Hans-Georg Schweiger, 2022. "Calculating Available Charge and Energy of Lithium-Ion Cells Based on OCV and Internal Resistance," Energies, MDPI, vol. 15(21), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:7902-:d:952280
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    References listed on IDEAS

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    1. Noshin Omar & Peter Van den Bossche & Thierry Coosemans & Joeri Van Mierlo, 2013. "Peukert Revisited—Critical Appraisal and Need for Modification for Lithium-Ion Batteries," Energies, MDPI, vol. 6(11), pages 1-17, October.
    2. de Hoog, Joris & Timmermans, Jean-Marc & Ioan-Stroe, Daniel & Swierczynski, Maciej & Jaguemont, Joris & Goutam, Shovon & Omar, Noshin & Van Mierlo, Joeri & Van Den Bossche, Peter, 2017. "Combined cycling and calendar capacity fade modeling of a Nickel-Manganese-Cobalt Oxide Cell with real-life profile validation," Applied Energy, Elsevier, vol. 200(C), pages 47-61.
    3. Jorge Nájera & Pablo Moreno-Torres & Marcos Lafoz & Rosa M. De Castro & Jaime R. Arribas, 2017. "Approach to Hybrid Energy Storage Systems Dimensioning for Urban Electric Buses Regarding Efficiency and Battery Aging," Energies, MDPI, vol. 10(11), pages 1-16, October.
    4. Gaizka Saldaña & José Ignacio San Martín & Inmaculada Zamora & Francisco Javier Asensio & Oier Oñederra, 2019. "Analysis of the Current Electric Battery Models for Electric Vehicle Simulation," Energies, MDPI, vol. 12(14), pages 1-27, July.
    5. Nataliya N. Yazvinskaya & Mikhail S. Lipkin & Nikolay E. Galushkin & Dmitriy N. Galushkin, 2022. "Peukert Generalized Equations Applicability with Due Consideration of Internal Resistance of Automotive-Grade Lithium-Ion Batteries for Their Capacity Evaluation," Energies, MDPI, vol. 15(8), pages 1-11, April.
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