Prediction method of energy replenishment duration based on user historical behavior
A kind of energy replenishment and historical technology, applied in the field of vehicle energy replenishment, can solve the problems of increasing operating costs and achieve the effect of avoiding the experience of power-on
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no. 1 example
[0063] see figure 1 , figure 1 It shows a schematic flow chart of the method for predicting the duration of replenishment based on the user's historical behavior in the first embodiment of the present invention, and the specific steps are as follows:
[0064] S101. Match the acquired current energy supplement request information of the user with the stored pieces of historical energy supplement data of the user.
[0065] The energy replenishment request information includes multiple factors that affect the duration of energy replenishment. Specifically, in this embodiment, the energy replenishment request information includes the following factors: energy replenishment request time, energy replenishment request location, and cruising range of the vehicle to be replenished. Of course, it can be understood that this embodiment does not limit the specific number of factors in the energy supplement request information, nor does it limit the specific types of factors in the energy...
no. 2 example
[0077] see figure 2 , figure 2 It shows a schematic flow chart of the method for predicting the duration of replenishment based on the user's historical behavior in the second embodiment of the present invention, and the specific steps are as follows:
[0078] S201. Determine the matching factor in the user's current energy replenishment request information.
[0079]In this embodiment, the energy replenishment request information specifically includes the energy replenishment request time A, the energy replenishment request location B, the cruising range C of the vehicle to be replenished, the interval between the return time of the vehicle and the first use after return, D, and the first driving destination after return E, weather conditions, F and other factors. For the above factors, the system will assign different weights to each factor from the perspective of affecting the "user's expected energy replenishment time point", and the sum of the weights of each factor is...
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