城轨列车模型的关键参数拟合研究

发布时间：2018-10-13 08:24

【摘要】：近年来,城市轨道交通领域的发展引领着城轨列车设计制造、信号设备研发生产等相关行业的飞速发展,越来越多的高校和研究机构从事轨道交通领域的基础研究和应用研究。列车动力学模型作为其研究的基础,对列车的运行控制有着极大的影响。在对城轨列车节能优化研究过程中,由于列车模型不够精确,仿真环境下理论节能效果与现场实测节能效果有所差异。因此,准确的列车模型对工程和理论研究具有深刻的意义。在总结了列车模型现有研究的基础上,根据列车的运行工况和数据特点,本文建立了符合实际列车运行情况的单质点动力学模型,将列车模型划分为惰行阶段模型、牵引阶段模型和制动阶段模型。将牵引阶段分为牵引建立和牵引切除阶段,其中,牵引建立阶段模型分为低速牵引建立阶段模型和高速牵引建立阶段模型。将列车模型划分为若干个模型,能够更准确的表述实际列车运行过程。针对参数拟合计算问题,本文提出了果蝇优化算法的一种改进型算法CIP-FOA(Fruit Fly Optimization Algorithm with Changing Iteration and Population),该算法采用改变步长半径的方式,从迭代和种群两个方面对步长进行改进。通过与其他算法进行了仿真对比分析,验证了 CIP-FOA在稳定性、计算精度和计算效率等方面较其他算法有明显优势。本文在分析处理的北京地铁亦庄线的夜间测试数据的基础上,应用CIP-FOA对列车基本阻力参数、低速牵引建立阶段、高速牵引建立阶段、牵引切除阶段共14个模型参数进行拟合计算。本文在建立的城轨列车动力学模型和提出的CIP-FOA的基础上,开发了"城轨列车动力学模型仿真软件",该软件用于参数拟合计算和模型的仿真验证工作。基于"城轨列车动力学模型仿真软件",对不同控制策略的列车运行数据进行仿真计算,通过仿真结果的对比和分析,验证了本模型符合列车的实际运行过程,良好的实验结果体现了本研究在工程规划设计和列车动力学模型性能预测方面的作用。
[Abstract]:In recent years, the development of urban rail transit has led the rapid development of urban rail train design and manufacture, signal equipment research and production and other related industries. More and more universities and research institutions are engaged in the basic research and application research in the field of rail transit. As the basis of the research, the train dynamics model has a great influence on the train operation control. In the course of energy saving optimization research of urban rail trains, due to the inaccuracy of train model, the effect of theoretical energy saving in simulation environment is different from that of field measurement. Therefore, the accurate train model has profound significance for engineering and theoretical research. On the basis of summarizing the existing research on the train model and according to the operating conditions and data characteristics of the train, this paper establishes a single mass point dynamic model which accords with the actual train operation, and divides the train model into the idling stage model. Traction stage model and braking stage model. The traction stage is divided into traction establishment and traction resection, in which the traction establishment stage model is divided into low speed traction establishment stage model and high speed traction establishment stage model. The train model can be divided into several models, which can more accurately describe the actual train operation process. To solve the problem of parameter fitting, this paper presents an improved algorithm, CIP-FOA (Fruit Fly Optimization Algorithm with Changing Iteration and Population), for the optimization algorithm of Drosophila melanogaster. The algorithm improves the step size in terms of iteration and population by changing the radius of step size. By comparing with other algorithms, it is proved that CIP-FOA has obvious advantages over other algorithms in terms of stability, accuracy and efficiency. On the basis of analyzing the night test data of Beijing Metro Yizhuang Line, this paper applies CIP-FOA to the basic resistance parameters of trains, the low speed traction establishment stage, the high speed traction establishment stage. A total of 14 model parameters were fitted and calculated in the traction resection stage. Based on the established dynamic model of urban rail train and the proposed CIP-FOA, this paper develops a simulation software for the dynamic model of urban rail train, which is used for parameter fitting calculation and simulation verification of the model. Based on the simulation software of urban rail train dynamics model, the train operation data with different control strategies are simulated and calculated. Through the comparison and analysis of the simulation results, it is verified that the model accords with the actual running process of the train. Good experimental results show the function of this study in engineering planning and performance prediction of train dynamics model.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U270.11;TP391.9

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