The invention provides a vehicle abnormity monitoring method based on driving data, which comprises the following steps: setting a variable A and a variable B to represent a vehicle use state; dividing the variable A and the variable B into a low gear, a middle gear and a high gear according to a certain numerical interval, and combining the low gear, the middle gear and the high gear to obtain nine vehicle use states; a remote monitoring platform is used for collecting actual driving data of a plurality of automobiles of the same model, and the variable A and the variable B of each charging of the corresponding automobile are calculated according to the driving data to form automobile use state data; constructing a state transition matrix according to the collected vehicle use state data of the vehicles of the same model, and judging whether the transition matrix is stable or not; and if the transfer matrix is stable, predicting the running condition of the vehicle in a future period of time according to the vehicle use state corresponding to the convergence state of the transfer matrix. According to the invention, the accuracy of vehicle remote monitoring can be improved, and the safety of vehicle use is improved.
本发明提供一种基于行驶数据的车辆异常监控方法,包括:设置变量A和变量B,以表征车辆使用状态;将所述变量A和所述变量B按照一定的数值区间分割为低档、中档和高档,并进行组合得到9种车辆使用状态;利用远程监控平台收集同一型号的多辆汽车实际的行驶数据,并根据所述行驶数据计算出对应车辆每一次充电的所述变量A和所述变量B,形成车辆使用状态数据;根据收集的同一型号车辆的所述车辆使用状态数据,构建状态转移矩阵,并判断所述转移矩阵是否稳定;如果所述转移矩阵稳定,则根据转移矩阵收敛状态对应的车辆使用状态,对车辆未来一段时间运行状况进行预测。本发明能提高车辆远程监测的精准性,提高车辆使用的安全性。
Vehicle abnormity monitoring method based on driving data
一种基于行驶数据的车辆异常监控方法
2022-12-02
Patent
Electronic Resource
Chinese
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