Charging scheme recommendation method and charging scheme recommendation system

Abstract

The invention relates to a charging scheme recommendation method and a charging scheme recommendation system. The charging scheme recommendation method comprises the following steps: obtaining big data of a new energy vehicle, big data of a charging pile and big data of a charging station, and analyzing the big data of the new energy vehicle to obtain charging habits, charging preferences and daily behavior tracks of a new energy vehicle user; judging whether the new energy vehicle needs to be charged or not by combining the electric quantity condition of the new energy vehicle, the big data of the charging pile and the big data of the charging station, and obtaining recommended station information, wherein the recommended charging station contained in the recommended station information conforms to the charging habit and charging preference of the new energy vehicle user and has the minimum influence on the daily behavior track of the new energy vehicle user; and sending the recommended station information to the new energy vehicle user. The charging scheme recommendation system comprises a cloud platform used for executing the charging scheme recommendation method. According to the invention, a proper charging station can be better recommended to a new energy vehicle user, so that the charging experience of the user is improved.

Description

technical field [0001] The invention belongs to the technical field of electric vehicle charging, and in particular relates to a method and system capable of recommending a suitable charging station for users of new energy vehicles. Background technique [0002] At present, new energy vehicles have received strong support from the state and are booming. According to the China Electricity Council, the proportion of new energy vehicles will reach 25% by 2025. In 2030, the sales volume of new energy vehicles is expected to exceed 15 million, and the number of existing vehicles will exceed 80 million. . According to the estimated ratio of 2:1 between vehicles and piles, the charging pile gap has reached 40 million. How to efficiently unify the needs of new energy car owners and the distribution and use of charging piles is imminent. The existence of big data, the Internet of Things and AI technology has digitized charging piles and vehicle information, and created prerequisites...

AI Technical Summary

Problems solved by technology

[0003] At present, the charging behavior of new energy car owners is relatively random. It is often the case that the car is found to be out of power and then finds a station to find a pile. It may happen that the station or charging pile cannot meet their needs or is forced to change after a mistake. The method of finding a station It is often searched or navigated through the independent app of the pile company or the neutral charging pile aggregation platform

[0004] The current charging behavior, the relationship between users and pile companies is relatively fragmented, for example, the charging preferences and charging habits of actual users are not considered, and some algorithms can only be used in specific scenarios, such as the premise of user navigation. Therefore, the existing technology cannot intelligently recommend, push and analyze charging stations

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