The invention provides a ShuffleDarkNet37-SE new energy automobile power battery fault classification method, and the method comprises the steps: obtaining the initial data of a new energy automobile through an automobile sensor, and carrying out the preprocessing of the initial data of the new energy automobile; the method comprises the following steps of: after data preprocessing, inputting the data into a ShuffleDarkNet37-SE (ShuffleDarkNet37-SE) classification network; and after the classification network outputs a result, carrying out corresponding battery fault warning prompt. According to the ShuffleDarkNet37-SE method, the fault type of the new energy automobile battery can be judged, the timely early warning function is achieved, and automobile battery faults are reduced.

    本发明提出一种ShuffleDarkNet37‑SE的新能源汽车动力电池故障分类方法,该ShuffleDarkNet37‑SE方法包括:在汽车传感器获取新能源汽车初始数据后,对新能源汽车初始数据预处理;在数据预处理后,将数据输入ShuffleDarkNet37‑SE分类网络;在分类网络输出结果后,进行相应的电池故障告警提示。所提ShuffleDarkNet37‑SE方法能对新能源汽车电池的故障类型进行判断,实现及时预警功能,减少汽车电池故障。


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    Title :

    ShuffleDarkNet37-SE new energy automobile power battery fault classification method


    Additional title:

    一种ShuffleDarkNet37-SE的新能源汽车动力电池故障分类方法


    Contributors:
    LU QUAN (author) / CHEN SHAN (author) / YIN LINFEI (author) / HU LIKUN (author)

    Publication date :

    2023-12-01


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / B60L PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES , Antrieb von elektrisch angetriebenen Fahrzeugen / G01R Messen elektrischer Größen , MEASURING ELECTRIC VARIABLES / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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