The invention designs an electric vehicle high-power DC charging state monitoring and fault early warning method based on deep learning, and the method comprises the steps: firstly, carrying out the state monitoring of various parameters of electric vehicle high-power DC charging, and storing the parameters in a database; secondly, dividing data in the database into historical data and real-time data, and preprocessing the historical data and the real-time data; then, designing a CNN-BiGRU deep learning model to fully learn normal DC charging historical data, constructing a DC charging prediction model of the electric vehicle, and optimizing hyper-parameters of the model by adopting a sparrow search algorithm; then, formulating an evaluation standard of model prediction precision for judging the accuracy of model prediction, performing residual analysis on a model prediction value through a sliding window method, and determining a fault early warning threshold value and a rule suitable for direct current charging of the electric vehicle; and finally, applying the trained CNN-BiGRU prediction model to real-time high-power direct-current charging monitoring of the electric vehicle to realize fault early warning of the electric vehicle.
本发明设计一种基于深度学习的电动汽车大功率直流充电状态监测和故障预警方法,首先,对电动汽车大功率直流充电的各种参数进行状态监测,并将其存储至数据库;其次,将数据库中数据分为历史数据和实时数据,并进行预处理;然后,设计CNN‑BiGRU深度学习模型对正常直流充电历史数据进行充分的学习,构建电动汽车的直流充电预测模型,并采用麻雀搜索算法优化模型的超参数;接着,制定模型预测精度的评价标准,用来评判模型预测的准确性,并通过滑动窗口法对模型预测值进行残差分析,确定电动汽车直流充电合适的故障预警阈值和规则;最后,将训练好的CNN‑BiGRU预测模型应用到电动汽车实时大功率直流充电监测中,实现电动汽车的故障预警。
Electric vehicle high-power DC charging state monitoring and fault early warning method based on deep learning
基于深度学习的电动汽车大功率直流充电状态监测和故障预警方法
2022-01-07
Patent
Electronic Resource
Chinese
IPC: | B60L PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES , Antrieb von elektrisch angetriebenen Fahrzeugen |
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