Advanced health state intelligent diagnosis of lithium-ion batteries based on CNN-WNN-WBiLSTM model with attention mechanism

Advanced health state intelligent diagnosis of lithium-ion batteries based on CNN-WNN-WBiLSTM model with attention mechanism

Efforts to enhance Battery Management Systems (BMS) for Li-ion batteries in electric vehicles are crucial for ensuring safety and performance. Our study introduces CNN-WNN-WBiLSTM-AM, a novel time series model designed specifically for forecasting Li-Ion Battery State of Health (SOH). Integrating CN...

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Bibliographic Details
Main Authors: Walid Mchara, Mohamed Abdellatif Khalfa, Lazhar Manai
Format: Article
Language:English
Published: Taylor & Francis Group 2025-04-01
Series:Automatika
Subjects:
: Lithium-ion batteries
State of Health (SOH)
Convolutional Neural Network (CNN)
wavelet neural network (WNN)
Bi-Long Short-Term Memory (BiLSTM)
attention mechanism (AM)
Online Access:https://www.tandfonline.com/doi/10.1080/00051144.2025.2461821
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https://www.tandfonline.com/doi/10.1080/00051144.2025.2461821

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