A parking charging scheduling method and system for charging behavior recognition

By constructing a charging behavior recognition model and combining user historical data with real-time station resources, global optimization is performed, solving the problem of accurate matching in traditional parking and charging scheduling and improving scheduling efficiency and resource utilization in dynamic scenarios.

CN122453015APending Publication Date: 2026-07-24INTELLIGENT INTER CONNECTION TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
INTELLIGENT INTER CONNECTION TECH CO LTD
Filing Date
2026-04-24
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Traditional parking and charging scheduling cannot accurately match user needs with station resources. The scheduling method is fixed and lacks optimization, making it difficult to adapt to dynamic scenarios.

Method used

By collecting historical charging behavior data of users, an identification model is built to identify the charging mode of target users. Combined with the status data of charging piles and parking spaces, a matching and scheduling analysis is performed to conduct global optimization to determine the optimal scheduling parameters.

Benefits of technology

It enables precise matching of user charging needs with parking and charging resources at the depot, improving the efficiency and resource utilization of integrated parking and charging scheduling.

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Abstract

The application discloses a parking charging scheduling method and system for charging behavior recognition, relates to the technical field of electric vehicle charging scheduling, and comprises the following steps: collecting user historical charging behavior data and constructing a charging behavior recognition model, identifying target user behavior data by using the model to determine the charging behavior mode, and collecting charging pile working attribute data set and parking space state data in real time. The user charging behavior mode is matched and scheduled by combining the above data, charging scheduling resource parameter solution space is obtained, target charging scheduling resource parameters are determined by globally optimizing in the solution space, and scheduling optimization control is performed. The application solves the technical problems that the traditional parking charging scheduling cannot accurately match user demand and station resources, the scheduling mode is fixed and lacks optimization, and it is difficult to adapt to dynamic scenes, and achieves the technical effects that user charging demand and station parking charging resources are accurately matched, and parking charging integrated scheduling is more efficient and resource utilization is more reasonable.
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