城市轨道交通牵引计算仿真平台设计

耿鹏刘霞袁重阳

Design of Traction Calculation and Simulation Platform for Urban Rail Transit

GENG PengLIU XiaYUAN Chongyang
摘要:
[目的]在城市轨道交通项目设计初期,为了能够较准确的评估信号系统的运行指标,满足工程需求,有必要设计一套牵引计算仿真平台。[方法]该平台依托实际ATO(自动列车运行)算法,设计了一套牵引计算仿真平台,可以对城市轨道交通信号系统的旅行速度、追踪间隔等指标进行评估。模拟了一套简化的CBTC(基于通信的列车控制系统),包括运行计划制定、移动授权计算、安全控制模型输出,并最终自动生成牵引计算的CAD(计算机辅助设计)图纸,内容涵盖速度曲线、线路坡道、线路平面、追踪间隔等。[结果及结论]实现了仿真平台与控车算法库的集成。通过接口设计,有效提取ATO算法的关键参数,便于在不同项目应用中实施灵活调整。平台架构涵盖数据管理、逻辑运算、图表展示三大模块,且平台配备直观易用的交互界面,涵盖运营参数配置、列车参数设定、线路参数设定、追踪间隔计算、速度-距离曲线展示等功能,便于用户直接操控各环节。尽管仿真运行周期可按需调整,但动力学模型的计算周期仍维持与实际一致。
Abstracts:
[Objective] At the initial stage of urban rail transit projects, it is essential to design a traction calculation simulation platform to accurately evaluate the operational indicators of the signaling system and meet engineering requirements. [Method] Based on a practical ATO (automatic train operation) algorithm, a platform is designed to assess indicators such as operating speed and headway in urban rail transit signaling systems. A simplified CBTC (communication-based train control) system is simulated, incorporating operational planning formulation, movement authorization computation, safety control model outputs, and the automated generation of traction calculation CAD (computer-aided design) drawings. These drawings include details on speed curves, track gradients, track layout, and headway intervals. [Result & Conclusion] The integration of simulation platform and train control algorithm library is successfully achieved. Key parameters of the ATO algorithm are effectively extracted through interface design, facilitating flexible adjustments for different project applications. The platform architecture comprises three main modules: data management, logic processing, and graphical display. It is equipped with an intuitive and user-friendly interface that supports operations such as configuring operational parameters, setting train and track parameters, calculating headways, and displaying speed-distance curves. This design enables users to directly control each stage of the process. Although the simulation running cycle can be adjusted as needed, the computation cycle of the dynamics model remains consistent with real-world operations.
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