The invention discloses a multi-fault risk assessment and early warning method for a power battery, and the method comprises the steps: requesting the recent life cycle data of an in-service electric vehicle power battery from a cloud server, carrying out the data preprocessing, and obtaining a temperature value of any single battery in the power battery through an interpolation method; differentiating the voltage value and the temperature value of any battery monomer to obtain a fault discrimination signal; establishing a multi-fault risk discrimination model based on the fault discrimination signal to calculate absolute fault degree scores corresponding to different faults of the battery; performing statistics on data distribution of various battery faults and fault degree scores, determining a fault grading range according to a distribution result, and drawing a multi-fault risk early warning graph; and carrying out early warning on results in a specific fault grading range according to severity. According to the method, various faults of the power battery can be evaluated and separated, battery maintenance and overhaul reference can be provided for a vehicle owner in time according to the multi-fault risk early warning graph, calculation is simple, deployment is convenient, and the method has practical application value.
本发明公开了一种动力电池多故障风险评估及预警方法,包括:向云端服务器请求在役电动汽车动力电池近期生命周期数据,并进行数据预处理,通过插值法得到动力电池内任意电池单体的温度值;对任意电池单体的电压值和温度值进行差分化后得到故障判别信号;基于故障判别信号建立多故障风险判别模型以计算电池不同故障对应的绝对故障程度分数;统计各类电池故障及故障程度分数的数据分布,由分布结果确定故障分级范围并绘制多故障风险预警图;对处于特定故障分级范围的结果按严重程度进行预警。本发明可以对动力电池的多种故障进行评估与分离,依据多故障风险预警图可及时为车主提供电池维护和检修参考,计算简单、部署方便,具备实际应用价值。
Power battery multi-fault risk assessment and early warning method
一种动力电池多故障风险评估及预警方法
2025-01-28
Patent
Electronic Resource
Chinese
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