基于SDS信息的新型汽车电池材料火灾危险性评估

J. Kida, T. Akitsu
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引用次数: 1

摘要

本研究使用安全数据表(SDS),其中描述了与化学物质相关的特性和危害,以确定与电池材料相关的危害。此外,我们还研究了是否可以仅使用sds来预测车载电池引起的电动汽车火灾。此外,我们的目标是利用基于sds的人工智能(AI)方法克服电动汽车火灾预测的局限性。我们发现,使用sds可以准确预测电池材料引起的火灾;然而,由热失控或未知或人为原因引起的火灾无法仅由sds预测。结果表明,当人工智能用于预测和扑灭电动汽车火灾时,重要的是要考虑与电池材料相关的危害,并分析过去发生的火灾以及有效的灭火方法。虽然在提供给人工智能的信息的组织和发展阶段存在限制,但如果实施,它可以应用于预测电动汽车和其他设备的火灾。
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Fire Hazard Assessment of New Automotive Battery Materials Using SDS Information
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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