A method based on improved ant lion optimization and support vector regression for remaining useful life estimation of lithium‐ion batteries

A method based on improved ant lion optimization and support vector regression for remaining useful life estimation of lithium‐ion batteries

Abstract Remaining useful life (RUL) prediction of lithium‐ion batteries (LIBs) plays a very important role in the prognostics and health management (PHM). Accurately predicting RUL of batteries can maintain and replace the batteries in advance to guarantee the safety and stability of the energy sto...

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Bibliographic Details
Main Authors: Yingzhou Wang, Yulong Ni, Na Li, Shuai Lu, Shude Zhang, Zhongbao Feng, Jianguo Wang
Format: Article
Language:English
Published: Wiley 2019-12-01
Series:Energy Science & Engineering
Subjects:
improved ant lion optimization
lithium‐ion battery
remaining useful life
support vector regression
Online Access:https://doi.org/10.1002/ese3.460

Internet

https://doi.org/10.1002/ese3.460

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