Public charging pile station grading method and device, equipment and storage medium

By extracting features from the reservation, order and collection data of public charging pile stations, and training machine learning models for hierarchical prediction, it solves the problem of automatic identification and grading of public charging pile stations in the existing technology, and realizes a user-friendly pile station type recognition and efficient authentication process.

CN119692858APending Publication Date: 2025-03-25FAW VOLKSWAGEN AUTOMOTIVE CO LTD
0 Cites 0 Cited by

Patent Information

Application Number
CN202411835183.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-13
Publication Date
2025-03-25

AI Technical Summary

Technical Problem

The automatic identification and grading of existing public charging pile stations is difficult to achieve, resulting in users being unable to effectively identify the pile station type, the certification cost is high and the cycle is long, and it is impossible to provide a good charging experience.

Method used

By extracting features from the reservation, order and collection data of the graded public charging pile stations, the machine learning model is trained, and the model is used to extract and grade prediction of the unclassified pile stations to dynamically determine the pile station level.

Benefits of technology

Automatic classification of public charging stations has been realized, the ability of users to identify the type of pile stations has been improved, the certification cost has been reduced, the charging experience has been improved, and the charging station construction and service quality have been promoted.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention provides a public charging pile station grading method and device, equipment and a storage medium. The method comprises the steps of extracting reservation features, collection features, order features and pile station features from a reservation table, an order table and a collection table of graded public charging pile stations, and taking the reservation features, the collection features, the order features and the pile station features as training data together with pile station grades; training the initial machine learning model by using the training data to obtain a trained machine learning model; extracting reservation features, collection features, order features and pile station features of the ungraded public charging pile stations from the reservation table, the order table and the collection table of the ungraded public charging pile stations to serve as feature data; inputting the feature data into a trained machine learning model to obtain grading probability information of the ungraded public charging pile stations; and determining the grades of the ungraded public charging pile stations according to the grading probability information. According to the invention, dynamic and automatic grading of the pile stations is realized.
Need to check novelty before this filing date? Find Prior Art