A Control Model for Metro Train Movements: The Piecewise Nonlinear Time-domain Model

Jinlin Liao, Jiajun Lin, Guilian Wu, Hao Chen, Shiyuan Ni, Tingting Lin, Lu Tang
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Abstract

Metros have been becoming a mainstream means of transportation in China. The research of various aspects of metro transportation has developed rapidly. However, how to construct a practical control model has always been a research hotspot. In this paper, we propose a piecewise nonlinear time-domain model (PNTM). This model describes a piecewise control process of the train driving in each section. The most notable feature of PNTM is that according to the electromagnetic principle of the motor, the acceleration process of the train is divided into three phases: constant torque, constant power, and natural characteristic. In each operation phase, speed, position, and instantaneous power are chosen to describe driving states of the train. Moreover, functional expressions instead of differential equation sets are used to formulate the driving states. Finally, the model is validated by numerical examples for comparison with the linear model and the measured data in real cases in Shanghai Metro Line 1 (SML1). The experimental results indicate that the correlation coefficients between PNTM and the measured data in terms of speed and power are 0.9874 and 0.9999, respectively, which are much higher than the 0.9251 and 0.9996 of the linear model.
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地铁列车运动控制模型:分段非线性时域模型
地铁已经成为中国的主流交通工具。地铁交通各方面的研究发展迅速。然而,如何构建一个实用的控制模型一直是一个研究热点。本文提出一种分段非线性时域模型(PNTM)。该模型描述了列车在各路段行驶的分段控制过程。PNTM最显著的特点是根据电机的电磁原理,将列车的加速过程分为恒转矩、恒功率和自然特性三个阶段。在每个运行阶段,选择速度、位置和瞬时功率来描述列车的行驶状态。此外,用函数表达式代替微分方程组来表示驱动状态。最后,通过数值算例与线性模型及上海地铁1号线实测数据的对比,对模型进行了验证。实验结果表明,PNTM与实测数据在转速和功率方面的相关系数分别为0.9874和0.9999,远高于线性模型的0.9251和0.9996。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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