Electric vehicle charging station recommendation method considering multiple factors and multiple scenes

Abstract

The invention relates to an electric vehicle charging station recommendation method considering multiple factors and multiple scenes, and belongs to the field of electric vehicle charging. The methodcomprises the steps of acquiring the current SOC and position of a vehicle of a user in real time; respectively entering an active recommendation mode and a passive recommendation mode according to whether a user initiates a charging recommendation request or not; in the active recommendation mode, when the current SOC of the vehicle is smaller than a set threshold value; or in the passive recommendation mode and when the user does not set the charging target, calculating and storing the score of each charging station according to the index value corresponding to each charging station and thecurrent weight corresponding to each index, and finally the charging station recommendation result of the user is obtained. Multiple factors are comprehensively considered, user preferences are combined, the distribution network load rate, the user behavior scene and the user application scene are considered, multiple targets such as the shortest user charging time, the lowest charging cost and the most balanced power grid load are achieved, and a recommendation scheme is intelligently provided for the user.

Description

technical field [0001] The invention relates to a method for recommending an electric vehicle charging station considering multiple factors and multiple scenarios, and belongs to the field of electric vehicle charging. Background technique [0002] In recent years, with the aggravation of air pollution and the reduction of fossil fuels, electric vehicles, as vehicles using electric energy, are becoming more and more popular among users because they do not pollute urban air, are less noisy and require less maintenance. Coupled with the active promotion of the government, electric vehicles are becoming more and more popular. [0003] However, due to technology, cost and other reasons, the average mileage of electric vehicles is significantly lower than that of fuel vehicles. Therefore, it is necessary to configure enough charging piles for electric vehicle users, so that users can easily find suitable charging piles when they have charging needs. It can also actively remind u...

AI Technical Summary

Problems solved by technology

This method uses the neural network model to determine the recommended charging station, but the neural network model is relatively complex and the interpretability is not strong

Moreover, both patents adopt the recommendation mode of user wake-up. In addition, the recommendation does not consider balancing the grid load, does not combine the time and scene of the user's charging recommendation request, and does not provide users with a variety of preferences to choose from.

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