State of charge estimation for lithium-ion battery using Time Series Transformer with De-noise De-stationary Inception Network-Reference-Cited by-同舟云学术

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State of charge estimation for lithium-ion battery using Time Series Transformer with De-noise De-stationary Inception Network

Published:2024-07 Issue: Volume:93 Page:112224
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Yi Zhihao^ORCID,Wang Liwei,Yang Kaitai

Publisher

Elsevier BV

Reference47 articles.

1. Lithium-ion battery state of charge (SoC) estimation with non-electrical parameter using uniform fiber bragg grating (FBG);Ee;J. Energy Storage,2021

2. An online SOC and capacity estimation method for aged lithium-ion battery pack considering cell inconsistency;Yang;J. Energy Storage,2020

3. A review of lithium-ion battery state of charge estimation based on deep learning: Directions for improvement and future trends;Liu;J. Energy Storage,2022

4. A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations;Hannan;Renew. Sustain. Energy Rev.,2017

5. Accounting for lithium-ion battery degradation in electric vehicle charging optimization;Hoke;IEEE J. Emerg. Sel. Top. Power Electron.,2014

Cited by 1 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. A novel temporal-frequency dual attention mechanism network for state of charge estimation of lithium-ion battery;Journal of Power Sources;2024-12

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