Ensemble Learning for Precise State-of-Charge Estimation in Electric Vehicles Lithium-Ion Batteries Considering Uncertainty

<p dir="ltr">Accurate state-of-charge (SoC) estimation is crucial for enhancing the performance, longevity, safety, and reliability of lithium-ion batteries (LiBs) in electric vehicles (EVs). This study presents a comprehensive machine learning (ML)-based approach for SoC estimation...

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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 Automotive engineering Electrical engineering Information and computing sciences Artificial intelligence Machine learning electric vehicles state-of-charge lithium-ion batteries ensemble model Extra Tree Regressor light gradient boosting machine uncertainty quantification Uncertainty Estimation Accuracy Data models Batteries Reliability Ensemble learning Computational modeling State of charge Robustness
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Ensemble Learning for Precise State-of-Charge Estimation in Electric Vehicles Lithium-Ion Batteries Considering Uncertainty

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