Micro-Internal Short Circuit Detection in Lithium-Ion Batteries Based on <i>k</i>-Nearest Neighbor Method

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Other Title
  • <i>k</i> 近傍法を用いたリチウムイオン電池の微小内部短絡検出

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Description

<p> Internal short circuit that occurs inside lithium-ion batteries is known as one of the causes of thermal runaway. If micro-internal short circuits can be detected, the anomalies at very early stage can be known, and it will contribute to improved safety when using lithium-ion batteries. The purpose of this study is to fabricate a software architecture that can detect micro-internal short circuits of lithium-ion batteries during flight with a view to application to electric aircraft that require high safety. In this research, we first prepared a new lithium-ion battery and another lithium-ion battery of the same model that was intentionally deteriorated to make it easy to cause an internal short circuit. Next, we designed four features which denote a characteristic voltage behavior when the micro-internal short circuit occurs. A large feature value was obtained from the deteriorated battery, while such a value could not be obtained from the new battery. Therefore, we considered new batteries to be normal specimens, and tried to detect the abnormality of the deteriorated battery by k nearest neighborhood method. As a result, it was shown that micro-internal short circuits of lithium-ion batteries can be detected based on the features describing the behavior of the abnormal voltage change by the micro-internal short circuit.</p>

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Details 詳細情報について

  • CRID
    1390860940787675008
  • DOI
    10.32146/bdajcs.12.1
  • ISSN
    24343382
    21864195
  • Text Lang
    ja
  • Article Type
    journal article
  • Data Source
    • JaLC
    • KAKEN
  • Abstract License Flag
    Disallowed

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