Parametrization of equivalent circuit models for lithium-ion batteries using galvanostatic intermittent titration technique

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F26%3A0198148" target="_blank" >RIV/00216305:26220/26:0198148 - isvavai.cz</a>

Result on the web

<a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2025_sbornik_1.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2025_sbornik_1.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Parametrization of equivalent circuit models for lithium-ion batteries using galvanostatic intermittent titration technique

Original language description

This study presents an experimental methodology for parameterizing an Equivalent Circuit Model (ECM) of lithium-ion (Li-ion) batteries using the Galvanostatic Intermittent Titration Technique (GITT). ECMs are widely used for battery modeling due to their ability to approximate battery behavior with relatively low computational complexity. However, their accuracy strongly depends on precise identification of internal resistances and time constants, which define transient responses related to charge transfer and diffusion processes. In this work, a 3RC ECM configuration is employed to capture both fast and slow relaxation effects, enabling a more detailed characterization of the battery’s dynamic behavior. The experimental procedure consists of applying controlled current pulses followed by relaxation periods, during which voltage recovery is analyzed to extract key parameters. To refine the extracted values and ensure an optimal match between the model and measured voltage response, an iterative optimization process is applied, minimizing the discrepancy between simulated and experimental data. The proposed approach significantly enhances the accuracy of ECM parameterization, leading to a more reliable representation of lithium-ion battery dynamics across different States-of-Charge (SOC). The findings of this study contribute to improved state estimation, enhanced predictive maintenance, and more effective battery management strategies, ultimately supporting the optimization of energy storage systems and advancing battery performance modeling.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

20201 - Electrical and electronic engineering

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings I of the 31st Conference STUDENT EEICT 2025

ISBN

978-80-214-6321-9

ISSN

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e-ISSN

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Number of pages

5

Pages from-to

271-275

Publisher name

Brno University of Technology, Faculty of Electrical Engineering and Communication

Place of publication

Brno

Event location

Brno

Event date

Apr 29, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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