Parameter Identification and Open‐Circuit Voltage Estimation of Lithium‐Ion Battery Circuit Model Based on Multi‐Innovation Theory

ABSTRACT Accurate battery modeling is essential for battery management systems to evaluate performance under varying conditions and to enhance operational efficiency and safety. This paper studies online parameter identification and open‐circuit voltage estimation using a first‐order equivalent circuit model with hybrid pulse power characterization testing, proposing a multi‐innovation stochastic gradient algorithm that combines the multi‐innovation theory with stochastic gradient identification for lithium‐ion battery parameter estimation. By incorporating a convergence factor, a modified algorithm is developed to improve estimation accuracy and convergence speed, with experimental validation through constant‐current and pulse‐discharge data demonstrating high estimation accuracy and robust performance, indicating strong potential for practical battery management applications.

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Publication Details

Journal
International Journal of Circuit Theory and Applications
Published
2025-09-16
DOI
https://doi.org/10.1002/cta.70128
Citations
24
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
16.39
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article

Parameter Identification and Open‐Circuit Voltage Estimation of Lithium‐Ion Battery Circuit Model Based on Multi‐Innovation Theory

Ling Xu, You Zou
24 citations
International Journal of Circuit Theory and Applications
Advanced Battery Technologies Research
16.39
article

Parameter Identification and Open‐Circuit Voltage Estimation of Lithium‐Ion Battery Circuit Model Based on Multi‐Innovation Theory

Ling Xu, You Zou
article en
24 citations

Abstract

ABSTRACT Accurate battery modeling is essential for battery management systems to evaluate performance under varying conditions and to enhance operational efficiency and safety. This paper studies online parameter identification and open‐circuit voltage estimation using a first‐order equivalent circuit model with hybrid pulse power characterization testing, proposing a multi‐innovation stochastic gradient algorithm that combines the multi‐innovation theory with stochastic gradient identification for lithium‐ion battery parameter estimation. By incorporating a convergence factor, a modified algorithm is developed to improve estimation accuracy and convergence speed, with experimental validation through constant‐current and pulse‐discharge data demonstrating high estimation accuracy and robust performance, indicating strong potential for practical battery management applications.

International Journal of Circuit Theory and Applications
Wuhan Donghu University (CN), Changzhou University (CN)
Openalex Percentile: Top 1%
Advanced Battery Technologies Research
16.39
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