The invention relates to an exception recognition method and device, computer equipment, a storage medium and a program product. The method comprises the steps of obtaining monitoring data of a battery system of a target vehicle in a monitoring time period, performing data segmentation on the monitoring data according to a preset SOC classification interval and a preset temperature interval to obtain a plurality of data segments, and determining whether the battery system is abnormal or not according to the plurality of data segments. According to the method, the monitoring data are segmented, so that a more detailed anomaly determination strategy can be made for various vehicles, the anomaly determination accuracy is improved, the monitoring data are segmented according to the temperature and the SOC, and the data classification efficiency and accuracy are improved.
本申请涉及一种异常识别方法、装置、计算机设备、存储介质和程序产品。所述方法包括:获取目标车辆的电池系统在监测时间段内的监测数据,从而根据预设的荷电状态值SOC分类区间和预设的温度区间对监测数据进行数据分段,得到多个数据段,进而根据多个数据段,确定电池系统是否异常。通过对监测数据进行数据分段,便于针对各类车辆制定更加细化的异常确定策略,从而提高异常确定的准确度,且根据温度和SOC对监测数据进行数据分段,提高了数据分类的效率和准确度。
Abnormal recognition method and device, computer equipment, storage medium and program product
异常识别方法、装置、计算机设备、存储介质和程序产品
2024-12-27
Patent
Electronic Resource
Chinese
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