State of Health Estimation for Lithium-Ion Batteries Using an Explainable XGBoost Model with Parameter Optimization
Accurate and reliable estimation of the state of health (SOH) of lithium-ion batteries is crucial for ensuring safety and preventing potential failures of power sources in electric vehicles. However, current data-driven SOH estimation methods face challenges related to adaptiveness and interpretabil...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
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| Series: | Batteries |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-0105/10/11/394 |
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