State of health estimation of Lithium-ion batteries: A review of data-driven methods
Author:
Affiliation:
1. Plovdiv University "Paisii Hilendarski",Faculty of Physics and Technology,Department of Electronics, Communications and Information Technology,Plovdiv,Bulgaria,4000
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10278503/10278560/10279026.pdf?arnumber=10279026
Reference50 articles.
1. State of Health Estimation of Lithium-Ion Batteries Using a Multi-Feature-Extraction Strategy and PSO-NARXNN;ren;Batteries,2023
2. Accelerated state of health estimation of second life lithium-ion batteries via electrochemical impedance spectroscopy tests and machine learning techniques
3. An overview of data-driven battery health estimation technology for battery management system
4. Electrical Equivalent Circuit Models of Lithium-ion Battery
5. Deep learning networks for capacity estimation for monitoring SOH of Li-ion batteries for electric vehicles;kaur;Int J Energy Res,2020
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1. Lithium-ion Battery State of Health Estimation Using Support Vector Regression(SVR);2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE);2023-11-02
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