Adaptive Online State of Charge Estimation of EVs Lithium-Ion Batteries with Deep Recurrent Neural Networks

Adaptive Online State of Charge Estimation of EVs Lithium-Ion Batteries with Deep Recurrent Neural Networks

The State of Charge (SOC) estimation is a significant issue for safe performance and the lifespan of Lithium-ion (Li-ion) batteries. In this paper, a Robust Adaptive Online Long Short-Term Memory (RoLSTM) method is proposed to extract SOC estimation for Li-ion Batteries in Electric Vehicles (EVs). T...

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Bibliographic Details
Main Authors: Gelareh Javid, Djaffar Ould Abdeslam, Michel Basset
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Energies
Subjects:
electric vehicles (EVs)
Lithium-ion (Li-ion)
state of charge (SOC)
Recurrent Neural Network (RNN)
Long Short-Term memory (LSTM)
robust and adaptive online gradient learning method (RoAdam)
Online Access:https://www.mdpi.com/1996-1073/14/3/758

Internet

https://www.mdpi.com/1996-1073/14/3/758

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