Online model-based estimation of state-of-charge and open-circuit voltage of lithium-ion batteries in electric vehicles

Hongwen He*, Xiaowei Zhang, Rui Xiong, Yongli Xu, Hongqiang Guo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

434 Citations (Scopus)

Abstract

This paper presents a method to estimate the state-of-charge (SOC) of a lithium-ion battery, based on an online identification of its open-circuit voltage (OCV), according to the battery's intrinsic relationship between the SOC and the OCV for application in electric vehicles. Firstly an equivalent circuit model with n RC networks is employed modeling the polarization characteristic and the dynamic behavior of the lithium-ion battery, the corresponding equations are built to describe its electric behavior and a recursive function is deduced for the online identification of the OCV, which is implemented by a recursive least squares (RLS) algorithm with an optimal forgetting factor. The models with different RC networks are evaluated based on the terminal voltage comparisons between the model-based simulation and the experiment. Then the OCV-SOC lookup table is built based on the experimental data performed by a linear interpolation of the battery voltages at the same SOC during two consecutive discharge and charge cycles. Finally a verifying experiment is carried out based on nine Urban Dynamometer Driving Schedules. It indicates that the proposed method can ensure an acceptable accuracy of SOC estimation for online application with a maximum error being less than 5.0%.

Original languageEnglish
Pages (from-to)310-318
Number of pages9
JournalEnergy
Volume39
Issue number1
DOIs
Publication statusPublished - Mar 2012

Keywords

  • Electric vehicles
  • Equivalent circuit model
  • Online estimation
  • Open-circuit voltage
  • State-of-charge

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