A Lithium-ion Battery SOC Estimation Method Involving Battery Internal Temperature

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1 Citation (Scopus)

Abstract

Accurate estimating the state of charge(SOC) of lithium-ion batteries is important for battery management systems. The SOC estimation generally considers ambient temperature instead of internal temperature parameter due to the difficulty of capturing internal temperature. Thanks to a recent work capturing internal temperature, this work proposes a method of SOC estimation for lithium-ion batteries based on internal temperature which has not been investigated in the existing studies. Three kinds of tests are carried out at 0°C, 15°C, 25 °C, 35°C and 45 °C, including maximum capacity test, open circuit voltage test, and dynamic stress test (DST). Subsequently, the second-order RC equivalent circuit model of the battery is established. And the parameters of the battery model are identified by the forgetting factor recursive least squares (FFRLS) algorithm considering the ambient temperature and the internal temperature. Finally, the SOC of the lithium-ion battery is estimated using the DST test data at 0 °C, 25 °C and 45 °C, the model parameter identification results at the two temperatures, and the EKF algorithm. The experimental results show that the SOC estimation accuracy involving the internal temperature of the battery is higher than the SOC estimation accuracy considering the ambient temperature.

Original languageEnglish
Title of host publication2022 6th CAA International Conference on Vehicular Control and Intelligence, CVCI 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665453745
DOIs
Publication statusPublished - 2022
Event6th CAA International Conference on Vehicular Control and Intelligence, CVCI 2022 - Nanjing, China
Duration: 28 Oct 202230 Oct 2022

Publication series

Name2022 6th CAA International Conference on Vehicular Control and Intelligence, CVCI 2022

Conference

Conference6th CAA International Conference on Vehicular Control and Intelligence, CVCI 2022
Country/TerritoryChina
CityNanjing
Period28/10/2230/10/22

Keywords

  • Extended Kalman Filter
  • Forgetting Factor Recursive Least Squares
  • Internal temperature
  • Lithium-ion battery
  • SOC

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