Probabilistic neural network-based flexible estimation of lithium-ion battery capacity considering multidimensional charging habits-Reference-Cited by-同舟云学术

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Probabilistic neural network-based flexible estimation of lithium-ion battery capacity considering multidimensional charging habits

Published:2024-05 Issue: Volume:294 Page:130881
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Li Qingbo,Zhong Jun,Du Jinqiao,Yi Yong,Tian Jie,Li Yan,Lai Chunyan^ORCID,Lu Taolin,Xie Jingying^ORCID

Publisher

Elsevier BV

Reference42 articles.

1. 30 Years of lithium-ion batteries;Li;Adv Mater,2018

2. The lithium-ion battery: state of the art and future perspectives;Zubi;Renew Sustain Energy Rev,2018

3. Battery capacity estimation using 10-second relaxation voltage and a convolutional neural network;Fan;Appl Energy,2023

4. A flexible battery capacity estimation method based on partial voltage curves and polynomial fitting;Cao;Energy Build,2023

5. A review of the state of health for lithium-ion batteries: research status and suggestions;Tian;J Clean Prod,2020

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting the Future Capacity and Remaining Useful Life of Lithium-Ion Batteries Based on Deep Transfer Learning;Batteries;2024-08-28

2. A Deep Learning Model Based on the Introduction of Attention Mechanism is Used to Predict Lithium-Ion Battery SOC;Journal of The Electrochemical Society;2024-07-01

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