The invention discloses a vehicle endurance mileage prediction method and device, equipment and a storage medium, and the method comprises the steps: screening the real-time information of the driving state of a vehicle according to a first ensemble learning model, and obtaining the real-time influence data of the battery state; the battery state real-time influence data are characteristic data representing road conditions, driving habits, vehicle conditions and driving time, inputting the battery state real-time influence data and the battery state real-time information into a second integrated learning model for endurance mileage prediction, and obtaining the vehicle endurance mileage. According to the method, data information of different vehicle types can be analyzed, modeling and training for a single vehicle are not needed, and the training cost and the maintenance cost are low. According to the method, data are trained in an integrated learning model mode, the application range is wide, the training efficiency is high, the prediction model can be continuously adjusted and optimized by depending on an existing Internet of Vehicles big database, and the accuracy can be continuously improved.
本发明公开了一种车辆续航里程预测方法、装置、设备和存储介质,所述方法根据第一集成学习模型,对车辆行驶时的行驶状态实时信息进行筛选,得到电池状态实时影响数据,电池状态实时影响数据为表征路况、驾驶习惯、车况和行驶时间的特征数据,将电池状态实时影响数据和电池状态实时信息输入到第二集成学习模型进行续航里程预测,得到车辆续航里程。所述方法对不同车型的数据信息均可以进行分析,不需要针对单一车辆进行建模和训练,训练成本和维护成本低。所述方法还通过集成学习模型的方式对数据进行训练,适用范围广,训练效率高,且依靠现有车联网大数据库,预测模型可以不断调优,准确度会不断升高。
Vehicle endurance mileage prediction method and device, equipment and storage medium
一种车辆续航里程预测方法、装置、设备和存储介质
2021-09-03
Patent
Electronic Resource
Chinese
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