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Estimating the State of Charge of Lithium-Ion Batteries Based on the Transfer Function of the Voltage Response to the Current Pulse

Author

Listed:
  • Ivan Radaš

    (Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia)

  • Nicole Pilat

    (Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia)

  • Daren Gnjatović

    (Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia)

  • Viktor Šunde

    (Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia)

  • Željko Ban

    (Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia)

Abstract

There are several methods for estimating the SoC of lithium-ion batteries that use electrochemical battery models or artificial intelligence and intelligent algorithms. These methods have numerous advantages but are complex and computationally intensive. This paper presents a new method for estimating the SoC of lithium-ion batteries based on identifying the transfer function of the measured battery voltage response to the charging current pulse. It is assumed that the transfer function of the battery changes with the state of charge. In the learning phase, a reference table of known SoC s and associated transfer functions is created. The parameters of these transfer functions form the reference points in hyperspace. In the phase of determining the unknown SoC of the battery, the parameters of the measured transfer function form a point in hyperspace that is compared with the reference points of the transfer functions for known SoC s. The unknown SoC of the battery at the particular measurement time is obtained by finding the two reference points closest to the point of unknown SoC using the Euclidean distance and a linear interpolation based on this distance. The method is simple, computationally undemanding, insensitive to measurement noise, and has high accuracy in SoC estimation.

Suggested Citation

  • Ivan Radaš & Nicole Pilat & Daren Gnjatović & Viktor Šunde & Željko Ban, 2022. "Estimating the State of Charge of Lithium-Ion Batteries Based on the Transfer Function of the Voltage Response to the Current Pulse," Energies, MDPI, vol. 15(18), pages 1-14, September.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6495-:d:907619
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    References listed on IDEAS

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    1. 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.
    2. Longxing Wu & Kai Liu & Hui Pang & Jiamin Jin, 2021. "Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current Bias," Energies, MDPI, vol. 14(17), pages 1-12, August.
    3. Waag, Wladislaw & Käbitz, Stefan & Sauer, Dirk Uwe, 2013. "Experimental investigation of the lithium-ion battery impedance characteristic at various conditions and aging states and its influence on the application," Applied Energy, Elsevier, vol. 102(C), pages 885-897.
    4. Ng, Kong Soon & Moo, Chin-Sien & Chen, Yi-Ping & Hsieh, Yao-Ching, 2009. "Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries," Applied Energy, Elsevier, vol. 86(9), pages 1506-1511, September.
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