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Destruction mechanism of the internal structure in Lithium-ion batteries used in aviation industry

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  • Swornowski, Paweł J.

Abstract

In the article, the reasons for destruction of the internal structure in Lithium-ion batteries used in aviation industry have been explained. They manifest themselves in the battery's overheating, and in extreme cases they result in explosion. The report presents the results of experiments, which consisted in subjecting the tested Lithium-ion battery to vibration over a specified period of time and observing the changes of temperature inside it with the use of a thermal infrared camera. Another focal point of the study was the influence of vibrations on voltage change in relation to variable current load, and the influence of ambient temperature change on the Lithium-ion battery's voltage change. It has also been demonstrated that vibrations can damage the control electronics of the Lithium-ion battery. Moreover, the mechanism by which potentially dangerous thermal hot spots are formed in a Lithium-ion battery has been presented, as well as an uncertainty analysis of all measurement results.

Suggested Citation

  • Swornowski, Paweł J., 2017. "Destruction mechanism of the internal structure in Lithium-ion batteries used in aviation industry," Energy, Elsevier, vol. 122(C), pages 779-786.
    • Handle: RePEc:eee:energy:v:122:y:2017:i:c:p:779-786
    DOI: 10.1016/j.energy.2017.01.121
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    References listed on IDEAS

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    1. Feng, Xuning & Lu, Languang & Ouyang, Minggao & Li, Jiangqiu & He, Xiangming, 2016. "A 3D thermal runaway propagation model for a large format lithium ion battery module," Energy, Elsevier, vol. 115(P1), pages 194-208.
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    Cited by:

    1. Li, Niansi & Liu, Xiaoyong & Yu, Bendong & Li, Liang & Xu, Jianqiang & Tan, Qiong, 2021. "Study on the environmental adaptability of lithium-ion battery powered UAV under extreme temperature conditions," Energy, Elsevier, vol. 219(C).
    2. Lijun Zhang & Zhongqiang Mu & Xiangyu Gao, 2018. "Coupling Analysis and Performance Study of Commercial 18650 Lithium-Ion Batteries under Conditions of Temperature and Vibration," Energies, MDPI, vol. 11(10), pages 1-27, October.
    3. Ma, Qiuhui & Zheng, Ying & Yang, Weidong & Zhang, Yong & Zhang, Hong, 2021. "Remaining useful life prediction of lithium battery based on capacity regeneration point detection," Energy, Elsevier, vol. 234(C).
    4. Chuang Sun & An Qu & Jun Zhang & Qiyang Shi & Zhenhong Jia, 2022. "Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Improved Variational Mode Decomposition and Machine Learning Algorithm," Energies, MDPI, vol. 16(1), pages 1-15, December.
    5. Shaheer Ansari & Afida Ayob & Molla Shahadat Hossain Lipu & Aini Hussain & Mohamad Hanif Md Saad, 2021. "Multi-Channel Profile Based Artificial Neural Network Approach for Remaining Useful Life Prediction of Electric Vehicle Lithium-Ion Batteries," Energies, MDPI, vol. 14(22), pages 1-22, November.

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