Early warning of battery failure based on venting signal-Reference-Cited by-同舟云学术

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Early warning of battery failure based on venting signal

Published:2023-03 Issue: Volume:59 Page:106536
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Huang Wensheng,Feng Xuning,Pan Yue,Jin Changyong,Sun Jieyu,Yao Jian,Wang Huaibin,Xu Chengshan,Jiang Fachao,Ouyang Minggao

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

Reference44 articles.

1. Thermal runaway mechanism of lithium ion battery for electric vehicles: a review[J];Feng;Energy Storage Mater.,2018

2. Brief review of batteries for XEV applications[J];Zhang;Etransportation,2019

3. Lithium-ion battery fast charging: a review[J];Anna;eTransportation,2019

4. A review of modeling, acquisition, and application of lithium-ion battery impedance for onboard battery management[J];Wang;eTransportation,2021

5. Multi-objective optimization design and experimental investigation for a parallel liquid cooling-based Lithium-ion battery module under fast charging[J];Chen;Appl. Therm. Eng.,2022

Cited by 27 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. Experimental study on thermal runaway venting behaviour of LiNi0.8Co0.1Mn0.1O2 pouch cell under different sealing edge directions;Journal of Power Sources;2024-11

2. Quantification of venting behavior of cylindrical lithium-ion and sodium-ion batteries during thermal runaway;Journal of Power Sources;2024-09

3. In situ measurement and modeling of internal thermal runaway propagation within lithium-ion cells under local overheating conditions;Journal of Power Sources;2024-09

4. A comprehensive review on thermal runaway model of a lithium-ion battery: Mechanism, thermal, mechanical, propagation, gas venting and combustion;Renewable Energy;2024-08

5. Cloud-based battery failure prediction and early warning using multi-source signals and machine learning;Journal of Energy Storage;2024-07

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