Hybrid Tree-Based Machine Learning Models for State-of-Charge and Core Temperature Estimation in EV Batteries

<p dir="ltr">Accurate estimation of State-of-Charge (SoC) and core temperature is fundamental to optimizing the performance, safety, and longevity of Lithium-Ion Batteries (LiBs), particularly in Electric Vehicles (EVs). Traditional estimation methods fail to account for the complex,...

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Bibliographic Details
Main Author:	Aya Haraz (22225036) (author)
Other Authors:	Khalid Abualsaud (16888701) (author), Ahmed M. Massoud (16896417) (author)
Published:	2025
Subjects:	Engineering Electrical engineering Electronics, sensors and digital hardware Information and computing sciences Artificial intelligence Data management and data science Machine learning electric vehicles state-of-charge estimation lithium-ion batteries core temperature tree-based model linear regression Gaussian multivariate copula battery management systems Computational modeling Accuracy Temperature measurement Uncertainty Data models Adaptation models Feature extraction Analytical models Training
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Hybrid Tree-Based Machine Learning Models for State-of-Charge and Core Temperature Estimation in EV Batteries

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