Improved LightGBM-Based Framework for Electric Vehicle Lithium-Ion Battery Remaining Useful Life Prediction Using Multi Health Indicators

Improved LightGBM-Based Framework for Electric Vehicle Lithium-Ion Battery Remaining Useful Life Prediction Using Multi Health Indicators

To improve the prediction accuracy and prediction speed of battery remaining useful life (RUL), this paper proposes an improved light gradient boosting machine (LightGBM)-based framework. Firstly, the features from the electrochemical impedance spectroscopy (EIS) and incremental capacity-differentia...

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Bibliographic Details
Main Authors: Huiqiao Liu, Qian Xiao, Yu Jin, Yunfei Mu, Jinhao Meng, Tianyu Zhang, Hongjie Jia, Remus Teodorescu
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Symmetry
Subjects:
electric vehicle
lithium-ion battery
remaining useful life prediction
multi health indicators
LightGBM
Online Access:https://www.mdpi.com/2073-8994/14/8/1584

Internet

https://www.mdpi.com/2073-8994/14/8/1584

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