Prediction of Battery SOH by CNN-BiLSTM Network Fused with Attention Mechanism

Prediction of Battery SOH by CNN-BiLSTM Network Fused with Attention Mechanism

During the use and management of lead–acid batteries, it is very important to carry out prediction and study of the state of the health (SOH) of the battery. To this end, this paper proposes a SOH prediction method for lead–acid batteries based on the CNN-BiLSTM-Attention model. The model utilizes t...

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Bibliographic Details
Main Authors: Shuo Sun, Junzhong Sun, Zongliang Wang, Zhiyong Zhou, Wei Cai
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Energies
Subjects:
state of health (SOH)
convolutional neural network (CNN)
bidirectional long short-term memory network (BiLSTM)
attention mechanism (Attention)
multi-step prediction
Online Access:https://www.mdpi.com/1996-1073/15/12/4428

Internet

https://www.mdpi.com/1996-1073/15/12/4428

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