Relative Entropy based Lithium-ion Battery Pack Short Circuit Detection for Electric Vehicle

Zhenyu Sun, Zhenpo Wang, Peng Liu, Zhaosheng Zhang, Shuo Wang, David G. Dorrell

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)

Abstract

The thermal runaway of an electric vehicle (EV) battery can cause severe loss of property and human life. A cell short circuit can lead to thermal runaway in a minutes. Therefore, battery short circuit detection systems are important for prevention and limitation of EV fire incidents. This paper proposes a short circuit detection and isolation method for lithium-ion battery packs based on relative entropy. The proposed data-driven method can identify the voltage drop behavior caused by the short circuit. It is verified using real-world data measured from electric vehicles which experienced thermal runaway causing a fire incident. The relative entropy method can recognize the data pattern in real time and give a short circuit alarm to the driver.

Original languageEnglish
Title of host publicationECCE 2020 - IEEE Energy Conversion Congress and Exposition
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5061-5067
Number of pages7
ISBN (Electronic)9781728158266
DOIs
Publication statusPublished - 11 Oct 2020
Event12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020 - Virtual, Detroit, United States
Duration: 11 Oct 202015 Oct 2020

Publication series

NameECCE 2020 - IEEE Energy Conversion Congress and Exposition

Conference

Conference12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020
Country/TerritoryUnited States
CityVirtual, Detroit
Period11/10/2015/10/20

Keywords

  • electric vehicles
  • fault diagnosis
  • relative entropy

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