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PyBatteryID – A Python Package for Data-Driven Battery Model Identification using LPV Framework Cover

PyBatteryID – A Python Package for Data-Driven Battery Model Identification using LPV Framework

Open Access
|Feb 2026

Figures & Tables

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Figure 1

A structural overview of the PyBatteryID package.

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Figure 2

Model identification results for a 2.85-Ah NMC battery cell; (a) and (b) show the identification and validation current profiles, respectively, and (c) compares the measured voltage with the simulated voltage obtained using an LTI and an LPV model.

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DOI: https://doi.org/10.5334/jors.595 | Journal eISSN: 2049-9647
Language: English
Submitted on: Jul 7, 2025
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Accepted on: Jan 21, 2026
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Published on: Feb 4, 2026
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2026 Muiz Sheikh, Tijs Donkers, Henk Jan Bergveld, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.