The invention provides a battery detection method, a prediction model training method and related equipment, and the method comprises the steps: obtaining the parameter information of a battery of a vehicle in a current time period, and the parameter information comprises the voltage, current, temperature and resistance of the battery; determining each first index value corresponding to the current time period according to the parameter information, and performing preset operation processing on the first index values of the same type to obtain each second index value; and inputting each first index value and each second index value into a prediction model, and determining whether the battery has a thermal runaway risk or not according to output information of the prediction model. In the application, the first index values including the mean value, the variance, the extreme value, the kurtosis and the skewness are determined through the temperature, the voltage, the resistance and the current of the battery, and the second index values are derived based on the first index values, that is, the thermal runaway of the battery is predicted through various parameters, so that the detection accuracy of the thermal runaway of the battery is improved.
本申请提供一种电池检测方法、预测模型训练方法和相关设备,该方法包括:获取车辆的电池在当前时间段内的参数信息,参数信息包括电池的电压、电流、温度以及电阻;根据参数信息确定当前时间段对应的各个第一指标值,并对相同类型的第一指标值进行预设运算的处理得到各个第二指标值;将各个第一指标值以及各个第二指标值输入至预测模型,并根据预测模型的输出信息确定电池是否存在热失控风险。本申请中,通过电池的温度、电压、电阻以及电流确定包括均值、方差、极值、峰度以及偏度的各个第一指标值,在基于各个第一指标值衍生出各个第二指标值,也即通过多种参数对电池的热失控进行预测,提高了电池热失控的检测准确性。
Battery detection method, prediction model training method and related equipment
电池检测方法、预测模型训练方法和相关设备
2024-05-24
Patent
Electronic Resource
Chinese
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