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

10 Citations (Scopus)
242 Downloads (Pure)

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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