Fire Science and Technology
Online ISSN : 1882-0492
Print ISSN : 0285-9521
ISSN-L : 0285-9521
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  • Juri Kida, Takashiro Akitsu
    2019 Volume 38 Issue 1 Pages 1-19
    Published: 2019
    Released: March 29, 2020
    JOURNALS FREE ACCESS
    This study uses a safety data sheet (SDS), which describes the characteristics and hazards associated with a chemical substance, to determine the hazards associated with battery materials. Furthermore, we investigated whether fires in electric vehicles caused by vehicle-mounted batteries can be predicted using SDSs alone. In addition, we aimed to overcome the limitations associated with fire prediction in electric vehicles using an SDS-based artificial intelligence (AI) method. We found that fires caused by battery material could be accurately predicted using SDSs; however, fires caused by thermal runaway or fires of unknown or artificial origins could not be predicted by SDSs alone. Results demonstrate that when AI is utilized for predicting and extinguishing fires in electric vehicles, it is important to consider the hazards associated with the battery material and also to analyze fires that have occurred in the past along with effective fire extinguishing methods. Although there are limitations at the organizational and developmental stages of information provided to AI, if implemented, it can be applied for predicting fires in electric vehicles and in other devices.
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  • Juri Kida, Takashiro Akitsu
    2019 Volume 38 Issue 1 Pages 21-25
    Published: 2019
    Released: March 29, 2020
    JOURNALS FREE ACCESS
    Download PDF (212K)
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