The invention discloses an electric bicycle battery identification method based on a fryze theory and 1DCNN. The method comprises the following steps: acquiring voltage and current data on a user bus in a current time period; segmenting voltage and current data according to a voltage forward zero crossing point; decomposing each section of current into active current and reactive current according to a fryze power theory; inputting each section of reactive current into a pre-trained identification model based on a one-dimensional convolutional neural network, and outputting an identification result; and averaging the output results of the reactive current sections, comparing the averaged results with a set threshold value, and if the average value of the results is greater than the set threshold value, proving that the battery of the electric bicycle is charged in the current time period. The method can eliminate the influence on the recognition of the battery of the electric bicycle when the high-power resistive equipment is accessed, improves the recognition accuracy of the battery of the electric bicycle, does not need to detect the switching event of the electric equipment, and relaxes the limitation on the recognition of the battery of the electric bicycle.

    本申请公开了一种基于fryze理论与1DCNN的电动自行车电池识别方法,该方法包括以下步骤:获取当前时间段用户总线上的电压、电流数据;按照电压正向过零点将电压、电流数据分段;根据fryze功率理论将各段电流分解为有功电流和无功电流;将各段无功电流输入到事先训练好的基于一维卷积神经网络的识别模型中,输出识别结果;将各段无功电流的输出结果取平均,与设定的阈值进行比较,若结果的平均值大于设定的阈值,证明当前时间段有电动自行车电池充电。本发明能够消除大功率阻性设备接入时对电动自行车电池识别的影响,提高电动自行车电池识别的准确率,且无需检测用电设备投切事件,放宽了对电动自行车电池识别的限制。


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    Title :

    Electric bicycle battery identification method based on fryze theory and 1DCNN


    Additional title:

    一种基于fryze理论与1DCNN的电动自行车电池识别方法


    Contributors:
    ZHU YONG (author) / WANG CANHUA (author) / CEN ZHENGJUN (author) / WU JINQUN (author) / LI JIN (author) / YANG FAJIN (author) / ZHANG JIAXIN (author) / TENG YANG (author) / HUANG FEI (author) / LIN SHIKANG (author)

    Publication date :

    2023-08-11


    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 / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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