An Enhanced Equivalent Circuit Model with Real-Time Parameter Identification for Battery State-of-Charge Estimation

Farshid Naseri, Erik Schaltz, Daniel-Ioan Stroe, Alejandro Gismero, Ebrahim Farjah

Research output: Contribution to journalJournal articleResearchpeer-review

168 Citations (Scopus)
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Abstract

This article introduces an efficient modeling approach based on the Wiener structure to reinforce the capacity of classical equivalent circuit models (ECMs) in capturing the nonlinearities of lithium-ion (Li-ion) batteries. The proposed block-oriented modeling architecture is composed of a simple linear ECM followed by a static output nonlinearity block, which helps achieving a superior nonlinear mapping property while maintaining the real-time efficiency. The observability of the established battery model is analytically proven. This article also introduces an efficient parameter estimator based on extended-kernel iterative recursive least squares algorithm for real-time estimation of the parameters of the proposed Wiener model. The proposed approach is applied for state-of-charge (SoC) estimation of 3.4-Ah 3.6-V nickel-manganese-cobalt-based Li-ion cells using the extended Kalman filter (EKF). The results show about 1.5% improvement in SoC estimation accuracy compared with the EKF algorithm based on the second-order ECM. A series of real-time tests are also carried out to demonstrate the computational efficiency of the proposed method.

Original languageEnglish
JournalI E E E Transactions on Industrial Electronics
Volume69
Issue number4
Pages (from-to)3743-3751
Number of pages9
ISSN0278-0046
DOIs
Publication statusPublished - Apr 2022

Keywords

  • Equivalent circuit model (ECM)
  • Wiener model
  • extended Kalman filter (EKF)
  • least squares
  • lithium-ion (Li-ion) battery
  • state of charge (SoC)

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