大数据在电池使用寿命预测中的应用研究  

Application of big data in battery life prediction

作　　者：杨永超 YANG Yongchao(Yien New Power Technology(Shandong)Co.,Ltd.,Jinan 250104,China)

机构地区：[1]亿恩新动力科技(山东)有限公司,山东济南250104

出　　处：《中国高新科技》2024年第23期12-14,共3页

摘　　要：为可靠掌握电池的使用情况,研究大数据在电池使用寿命预测中的应用。获取循环充放电情况下电池容量的变化数据,并采用大数据处理技术处理数据中异常数据,采用主成分分析方法提取处理后数据中的电池特征,将提取的特征输入相关向量机和粒子滤波算法中,通过两种算法的结合处理,实现电池使用寿命预测。测试结果显示:该方法具有较好的应用效果,预测结果的拟合优度结果均在0.933以上,均方根误差均在0.0075以下。In order to reliably grasp the usage of batteries,the application of big data in battery life prediction was studied.The variation data of battery capacity under cyclic charge and discharge were obtained,and the abnormal data in the data were processed by big data processing technology.The battery features in the processed data were extracted by principal component analysis method,and the extracted features were input into the correlation vector machine and particle filter algorithm.The service life prediction of the battery was realized through the combination of the two algorithms.The test results show that the method has a good application effect,and the goodness of fit of the predicted results is above 0.933,the root mean square error is less than 0.0075.

关 键 词：大数据 电池 使用寿命预测 

分 类 号：TM912[电气工程—电力电子与电力传动]