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

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

5 Citationer (Scopus)
215 Downloads (Pure)

Abstrakt

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.

OriginalsprogEngelsk
TidsskriftI E E E Transactions on Industrial Electronics
Vol/bind69
Udgave nummer4
Sider (fra-til)3743-3751
Antal sider9
ISSN0278-0046
DOI
StatusUdgivet - apr. 2022

Fingeraftryk

Dyk ned i forskningsemnerne om 'An Enhanced Equivalent Circuit Model with Real-Time Parameter Identification for Battery State-of-Charge Estimation'. Sammen danner de et unikt fingeraftryk.

Citationsformater