Predicting Remaining Useful Life of Lithium-Ion Batteries for Electric Vehicles Using Machine Learning Regression Models
Accurate prediction of a lithium-ion battery's remaining useful life (RUL) is essential for effectively managing and maintaining electric vehicles (EVs). By anticipating battery health and potential failures, we can optimize performance, enhance safety, and prevent costly breakdowns. Based on...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Technology and Education Galileo da Amazônia
2025-02-01
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| Series: | ITEGAM-JETIA |
| Online Access: | https://itegam-jetia.org/journal/index.php/jetia/article/view/1267 |
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