High precision state of health estimation of lithium-ion batteries based on strong correlation aging feature extraction and improved hybrid kernel function least squares support vector regression machine model-Reference-Cited by-同舟云学术

High precision state of health estimation of lithium-ion batteries based on strong correlation aging feature extraction and improved hybrid kernel function least squares support vector regression machine model

Published:2024-06 Issue: Volume:90 Page:111834
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Feng Renjun,Wang Shunli,Yu Chunmei,Hai Nan,Fernandez Carlos

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference39 articles.

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3. State of charge and state of health estimation strategies for lithium-ion batteries;Wang;International Journal of Low-carbon Technologies,2023

4. SOH prediction for Lithium-Ion batteries by using historical state and future load information with an AM-seq2seq model;Qian;Appl. Energy,2023

5. A fast impedance calculation-based battery state-of-health estimation method;Fu;IEEE Trans. Ind. Electron.,2022

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