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| Main Authors: | , |
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| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.17630214 |
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Table of Contents:
- <p><span>Due to a variety of internal and external battery impacts, it is now more challenging to accurately estimate the<br>State of Charge (SOC) and State of Health (SOH) of lithium-ion batteries used in Electric Vehicles (EVs). The<br>paper's primary goal is to accurately predict the lithium-ion battery's SOC and SOH. The first-order RC<br>electrical equivalent circuit model is taken into consideration for analysis and modelling in this work. In order<br>to estimate the true parameters and internal states of the battery, the Adaptive Nonlinear Observer (ANO) is<br>developed to transform nonlinear equations into linearized equations. The transfer function is then derived<br>from the linearized equations. The suggested ANO provides superior dynamic results when compared to the<br>Extended Kalman Filter (EKF), and the convergence rate is examined using the linear criterion. The<br>MATLAB/Simulink platform has been used to validate the simulation findings of the suggested ANO.</span> </p>