Characterization and identification towards dynamic-based electrical modeling of lithium-ion batteries

Chuanxin Fan, Kailong Liu*, Yaxing Ren, Qiao Peng*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Lithium-ion batteries are widely recognized as a crucial enabling technology for the advancement of electric vehicles and energy storage systems in the grid. The design of battery state estimation and control algorithms in battery management systems is usually based on battery models, which interpret crucial battery dynamics through the utilization of mathematical functions. Therefore, the investigation of battery dynamics with the purpose of battery system identification has garnered considerable attention in the realm of battery research. Characterization methods in terms of linear and nonlinear response of lithium-ion batteries have emerged as a prominent area of study in this field. This review has undertaken an analysis and discussion of characterization methods, with a particular focus on the motivation of battery system identification. Specifically, this work encompasses the incorporation of frequency domain nonlinear characterization methods and dynamics-based battery electrical models. The aim of this study is to establish a connection between the characterization and identification of battery systems for researchers and engineers specialized in the field of batteries, with the intention of promoting the advancement of efficient battery technology for real-world applications.
Original languageEnglish
Pages (from-to)738-758
JournalJournal of Energy Chemistry
Early online date04 Mar 2024
Publication statusPublished - 01 May 2024


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