自放电风险特征识别模型数据集

一种基于自放电异常风险特征的新能源汽车风险识别模型，通过构造自放电异常风险特征，通过计算参数项的方差熵一致性完成车辆运行过程中的自放电风险特征计算与安全量化，最终结合风险累计算法实现车辆风险特征的识别，并以此实现对车辆综合状态的精准判定与故障识别。数据量：4.97G。

A risk identification model for new energy vehicles (NEVs) based on abnormal self-discharge risk features. This model first constructs abnormal self-discharge risk features, then calculates the self-discharge risk characteristics and quantifies the safety status during vehicle operation by computing the variance-entropy consistency of parameter items. Ultimately, by integrating the risk accumulation algorithm, it achieves the identification of vehicle risk features, enabling accurate determination of the vehicle's comprehensive state and fault recognition. Data volume: 4.97 GB.

搜集汇总

背景与挑战

背景概述

该数据集用于新能源汽车自放电风险特征识别，通过计算参数项的方差熵一致性来量化安全风险，并利用风险累计算法实现车辆故障识别与状态判定。数据规模为4.97GB，包含39个文件。