A SA-PSO Based LS-SVM Method for Lithium-Ion Battery Lifetime Prediction
Author:
Affiliation:
1. School of Mechatronic Engineering and Automation, Shanghai University,Shanghai,China
2. College of Information Engineering, Zhejiang University of Technology,Hangzhou City, Zhejiang Province,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10398736/10398580/10398837.pdf?arnumber=10398837
Reference12 articles.
1. State of health and remaining useful life prediction for lithium-ion batteries based on differential thermal voltammetry and a long and short memory neural network
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3. Review on Health State Estimation and Life Prediction of Lithium-ion Batteries [J/OL];Qing;High voltage technology,2023
4. A Data-driven Indirect Prediction of the SOH and RUL of Lithium-ion Batteries [D];Yanru;North University of China,2022
5. Online transient stability fault screening based on support vector machine [J];Yanhong;Automation of electric power system,2019
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