A LSTM-STW and GS-LM Fusion Method for Lithium-Ion Battery RUL Prediction Based on EEMD

A LSTM-STW and GS-LM Fusion Method for Lithium-Ion Battery RUL Prediction Based on EEMD

To address inaccurate prediction in remaining useful life (RUL) in current Lithium-ion batteries, this paper develops a Long Short-Term Memory Network, Sliding Time Window (LSTM-STW) and Gaussian or Sine function, Levenberg-Marquardt algorithm (GS-LM) fusion batteries RUL prediction method based on...

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Bibliographic Details
Main Authors: Ling Mao, Jie Xu, Jiajun Chen, Jinbin Zhao, Yuebao Wu, Fengjun Yao
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Energies
Subjects:
LSTM-STW
GS-LM
lithium-ion battery
RUL prediction
EEMD
higher accuracy
Online Access:https://www.mdpi.com/1996-1073/13/9/2380

Internet

https://www.mdpi.com/1996-1073/13/9/2380

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