The invention discloses a power battery fault detection method, system and device and a storage medium. The method comprises the steps of constructing a signature matrix for battery time sequence data, extracting spatial features based on a convolutional auto-encoder, capturing data time sequence features based on a convolutional long short-term memory network, and reconstructing the signature matrix by using a decoder based on the spatial features extracted by the encoder and the time sequence features extracted by the convolutional long short-term memory network. The residual error between the initial signature matrix and the reconstruction matrix is utilized to detect and diagnose the abnormity, the power battery pack is monitored and analyzed on the electric vehicle monitoring platform, and the safety of the battery system is effectively improved.
本发明公开了一种动力电池故障检测方法、系统、装置及存储介质,包含对电池时序数据构建签名矩阵、基于卷积自编码器提取空间特征、基于卷积长短期记忆网络捕获数据时序特征、基于编码器提取的空间特征和卷积长短期记忆网络提取的时序特征利用解码器进行签名矩阵的重构、利用初始签名矩阵与重构矩阵之间残差对异常进行检测和诊断,在电动汽车监控平台对动力电池组进行监控与分析,有效助力电池系统的安全。
Power battery fault detection method, system and device and storage medium
动力电池故障检测方法、系统、装置及存储介质
2022-12-30
Patent
Electronic Resource
Chinese
IPC: | G01R Messen elektrischer Größen , MEASURING ELECTRIC VARIABLES / B60L PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES , Antrieb von elektrisch angetriebenen Fahrzeugen / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / H01M Verfahren oder Mittel, z.B. Batterien, für die direkte Umwandlung von chemischer in elektrische Energie , PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY |
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