State of charge estimation framework for lithium-ion batteries based on square root cubature Kalman filter under wide operation temperature range

Jiangwei Shen, Jian Xiong, Xing Shu, Guang Li, Yuanjian Zhang, Zheng Chen, Yonggang Liu

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Due to the significant influence of temperature on battery charging and discharging performance, exact evaluation of state of charge (SOC) under complex temperature environment becomes increasingly important. This paper develops an advanced framework to estimate the SOC for lithium-ion batteries with consideration of temperature variation. First, an accurate electrical model with wide temperature compensation is established, and a series of experiments are carried out under wide range time-varying temperature from −20°C to 60°C. Then, the genetic algorithm is leveraged to identify the temperature-dependent model parameters. On this basis, the battery SOC is accurately estimated based on the square root cubature Kalman filter algorithm. Finally, the availability of the proposed method at different temperatures is validated through a complicated mixed working cycle test, and the experimental results manifest that the devised framework can accurately evaluate SOC under wide time-varying temperature range with the maximum error of less than 2%.
Original languageEnglish
Pages (from-to)5586-5601
Number of pages16
JournalInternational Journal of Energy Research
Volume45
Issue number4
Early online date11 Nov 2020
DOIs
Publication statusPublished - 25 Mar 2021

Keywords

  • Fuel Technology
  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering

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