Real-Time Overcharge Warning and Early Thermal Runaway Prediction of Li-Ion Battery by Online Impedance Measurement.

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Title: Real-Time Overcharge Warning and Early Thermal Runaway Prediction of Li-Ion Battery by Online Impedance Measurement.
Authors: Lyu, Nawei1 lvnawei@icloud.com, Jin, Yang1 yangjin@zzu.edu.cn, Xiong, Rui2 rxiong@bit.edu.cn, Miao, Shan1 miaos@zzu.edu.cn, Gao, Jinfeng1 jfgao@zzu.edu.cn
Source: IEEE Transactions on Industrial Electronics. Feb2022, Vol. 69 Issue 2, p1929-1936. 8p.
Subjects: Energy density, Forecasting, Measurement, Lithium-ion batteries, Mathematical models
Abstract: A lithium-ion battery has advantages such as high energy density and long calendar life, but it suffers from the risk of thermal runaway. Overcharge-induced thermal runaway accidents hold a considerable percentage. This article discovers that the slope of the dynamic impedance in the frequency band of 30–90 Hz turns positive from negative when the cell just starts to overcharge and proposes the theoretical explanation. Taking 70 Hz impedance as an example, the thermal runaway accident can be successfully avoided by cutting off the charging when the slope turns positive from negative during charging. The warning time is 580 s ahead of the thermal runaway. This feature is easy to identify and requires no complex mathematical models and parameters. Besides, the prediction method based on this feature can be conducted by using an online dynamic impedance measurement device designed by us, which is suitable for large-scale applications. Thus, the overcharge-induced thermal runaway accidents can be avoided. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Industrial Electronics is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Label: Title
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  Data: Real-Time Overcharge Warning and Early Thermal Runaway Prediction of Li-Ion Battery by Online Impedance Measurement.
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  Data: <searchLink fieldCode="AR" term="%22Lyu%2C+Nawei%22">Lyu, Nawei</searchLink><relatesTo>1</relatesTo><i> lvnawei@icloud.com</i><br /><searchLink fieldCode="AR" term="%22Jin%2C+Yang%22">Jin, Yang</searchLink><relatesTo>1</relatesTo><i> yangjin@zzu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Xiong%2C+Rui%22">Xiong, Rui</searchLink><relatesTo>2</relatesTo><i> rxiong@bit.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Miao%2C+Shan%22">Miao, Shan</searchLink><relatesTo>1</relatesTo><i> miaos@zzu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Gao%2C+Jinfeng%22">Gao, Jinfeng</searchLink><relatesTo>1</relatesTo><i> jfgao@zzu.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Industrial+Electronics%22">IEEE Transactions on Industrial Electronics</searchLink>. Feb2022, Vol. 69 Issue 2, p1929-1936. 8p.
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  Data: <searchLink fieldCode="DE" term="%22Energy+density%22">Energy density</searchLink><br /><searchLink fieldCode="DE" term="%22Forecasting%22">Forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement%22">Measurement</searchLink><br /><searchLink fieldCode="DE" term="%22Lithium-ion+batteries%22">Lithium-ion batteries</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: A lithium-ion battery has advantages such as high energy density and long calendar life, but it suffers from the risk of thermal runaway. Overcharge-induced thermal runaway accidents hold a considerable percentage. This article discovers that the slope of the dynamic impedance in the frequency band of 30–90 Hz turns positive from negative when the cell just starts to overcharge and proposes the theoretical explanation. Taking 70 Hz impedance as an example, the thermal runaway accident can be successfully avoided by cutting off the charging when the slope turns positive from negative during charging. The warning time is 580 s ahead of the thermal runaway. This feature is easy to identify and requires no complex mathematical models and parameters. Besides, the prediction method based on this feature can be conducted by using an online dynamic impedance measurement device designed by us, which is suitable for large-scale applications. Thus, the overcharge-induced thermal runaway accidents can be avoided. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of IEEE Transactions on Industrial Electronics is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1109/TIE.2021.3062267
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 8
        StartPage: 1929
    Subjects:
      – SubjectFull: Energy density
        Type: general
      – SubjectFull: Forecasting
        Type: general
      – SubjectFull: Measurement
        Type: general
      – SubjectFull: Lithium-ion batteries
        Type: general
      – SubjectFull: Mathematical models
        Type: general
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      – TitleFull: Real-Time Overcharge Warning and Early Thermal Runaway Prediction of Li-Ion Battery by Online Impedance Measurement.
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            NameFull: Lyu, Nawei
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            NameFull: Jin, Yang
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            NameFull: Xiong, Rui
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            NameFull: Miao, Shan
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            NameFull: Gao, Jinfeng
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              M: 02
              Text: Feb2022
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              Y: 2022
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