Convolutional Transformer-Based Multiview Information Perception Framework for Lithium-Ion Battery State-of-Health Estimation
Author:
Affiliation:
1. Glasgow College, University of Electronic Science and Technology of China, Chengdu, China
2. Department of Industrial Engineering, Tsinghua University, Beijing, China
Funder
Innovation Fund of Glasgow College, University of Electronic Science and Technology of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/10012124/10198842.pdf?arnumber=10198842
Reference41 articles.
1. State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures
2. A novel method for state of health estimation of lithium-ion batteries based on improved LSTM and health indicators extraction
3. Online diagnosis of soft internal short circuits in series-connected battery packs using modified kernel principal component analysis
4. Research on Li-ion Battery Management System
5. Review of adaptive systems for lithium batteries State-of-Charge and State-of-Health estimation
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