Vehicle soc optimal scheduling method for smart rail line shared charging resource

By using a rolling time-domain scheduling framework and a spatiotemporal coupling model, the uncertainty problem of charging resource scheduling in shared intelligent rail depots for multiple lines is solved, achieving efficient, fair, and intelligent vehicle scheduling and improving capacity guarantee capabilities.

CN121882390BActive Publication Date: 2026-06-23SICHUAN SHUDAO NEW STANDARD RAIL GRP CO LTD +1
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Patent Information

Application Number
CN202610354403.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-03-23
Publication Date
2026-06-23
Estimated Expiration
2046-03-23

AI Technical Summary

Technical Problem

Existing technologies struggle to effectively coordinate vehicle charging in shared intelligent rail depots across multiple lines, resulting in low utilization of charging resources, delayed vehicle departures, disrupted train schedules, and a lack of dynamic adjustment capabilities.

Method used

A rolling time-domain scheduling framework is adopted, which combines vehicle operating status and real-time power grid data to construct unified status information and build a spatiotemporal coupling model of tracks and charging piles. Through joint optimization model decision-making, dynamic adjustment is achieved by determining vehicle parking, charging resource allocation and charging power.

Benefits of technology

It improves the efficiency of charging resource utilization, ensures vehicles are put into service on time, reduces scheduling conflicts, enhances the system's capacity guarantee capability, and has the ability to adapt to real-time disturbances.

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Abstract

The application provides a vehicle SOC optimal scheduling method for smart rail line shared charging resources, relates to the technical field of rail transit scheduling control, and solves the unreliable charging scheduling problem of multi-line smart rail vehicles in a shared charging resource environment. The method establishes a rolling horizon scheduling framework and constructs unified state information of vehicles, depots and power grids. Then, the target SOC of the vehicle executing the next task is calculated, and the corresponding charging scheduling constraint condition is constructed. A space-time coupling model of the track and charging pile resources is further constructed to represent the space-time resource occupation constraint. Based on the obtained or constructed various information, a joint optimization model is constructed and solved to synchronously decide the parking track and time period of the vehicle, the charging pile allocation, the charging time length and the charging power, generate corresponding instructions and issue them. The application significantly improves the utilization efficiency of the charging resources under the multi-line shared depot, and improves the vehicle on-line punctuality rate and the system operation capacity guarantee ability.
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