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

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Abstract

This paper introduces an efficient modeling approach based on Wiener structure to reinforce the capacity of the 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 realtime efficiency. The observability of the established battery model is analytically proven. This paper 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 NMC-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 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
Number of pages10
ISSN0278-0046
Publication statusE-pub ahead of print - 2021

Keywords

  • Equivalent circuit model
  • Extended Kalman filter
  • Least Squares
  • Lithium-ion Battery
  • State-of-Charge
  • Wiener Model

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