Regenerative Braking Energy Recovery System ofMetro Train Based on Dual-Mode PowerManagement

In order to fully utilize the regenerative braking energy of metro trains and stabilize the metro DC traction busbar voltage,a hybrid regenerative braking energy recovery system with a dual-mode power management strategy is proposed.Firstly,the construction of the hybrid regenerative braking energy recovery system is explained.Then,based on the power demand of low-voltage load in metro stations,a dual-mode power management strategy is proposed to allocate the reference power of each system according to the different working conditions,and the control methods of each system are set.Finally,the correctness and effectiveness of the dual-mode strategy are verified through simulation,and the proposed braking energy utilization scheme is compared with other singleform utilization schemes.The results illustrate that the hybrid system with the dual-mode strategy can effectively recycle the regenerative braking energy of metro train and inhibit the busbar voltage fluctuation;the proposed braking energy utilization scheme has certain advantages on energy recovery and DC bus voltage stabilization compared with other single-form schemes;the proposed power management strategy can correctly allocate the reference power of each system with a lower construction cost.

Comparative Analysis of Metro Passengers’Mobility Patterns and Jobs-housing Balance of Metropolitan

The advent of the big data era has provided many types of transportation datasets,such as metro smart card data,for studying residents’mobility and understanding how their mobility has been shaped and is shaping the urban space.In this paper,we use metro smart card data from two Chinese metropolises,Shanghai and Shenzhen.Five metro mobility indicators are introduced,and association rules are established to explore the mobility patterns.The proportion of people entering and exiting the station is used to measure the jobs-housing balance.It is found that the average travel distance and duration of Shanghai passengers are higher than those of Shenzhen,and the proportion of metro commuters in Shanghai is higher than that of Shenzhen.The jobs-housing spatial relationship in Shenzhen based on metro travel is more balanced than that in Shanghai.The fundamental reason for the differences between the two cities is the difference in urban morphology.Compared with the monocentric structure of Shanghai,the polycentric structure of Shenzhen results in more scattered travel hotspots and more diverse travel routes,which helps Shenzhen to have a better jobs-housing balance.This paper fills a gap in comparative research among Chinese cities based on transportation big data analysis.The results provide support for planning metro routes,adjusting urban structure and land use to form a more reasonable metro network,and balancing the jobs-housing spatial relationship.

Mechanical responses of underground carriageway structures due to construction of metro tunnels beneath the existing structure:A case study

To understand the mechanical response pattern of the existing structure and ground due to the construction of metro tunnels underneath,the finite difference method is adopted to study the torsional deformation and stress variation of the existing structure and the effect of underground carriageway structures on the surface subsidence.The curves of the maximum differential subsidence,torsion angle,and distortion of the cross-section of the existing structure show two peaks in succession during traversing of two metro tunnels beneath it.The torsion angle of the existing structure changes when the two tunnels traverse beneath it in opposite directions.The first traversing of the shield tunnel mainly induces the magnitude variation in torsional deformation of the existing structure,but the second traversing of the subsurface tunnel may cause a dynamic change in the magnitude and form of torsional deformation in the existing structure.The shielding effect can reduce the surface subsidence caused by metro tunnel excavation to a certain extent,and the development trend of subsidence becomes slower as the excavation continues.

Winding Function Theory Based Thrust Calculation on Nested-loop Secondary Linear Machine Adapted to Linear Metro

With advantages of strong drive capability,nested-loop secondary linear machine(NLS-LM)has great potentiality in linear metro.For its secondary structure with multiple loops,it is difficult to calculate the electromagnetic thrust of NLS-LM reasonably.Hence,in this paper,one thrust calculation method is proposed considering variable loop inductance and transient loop current.Firstly,to establish the secondary winding function,the modeling domain is confined to a limited range,and the equivalent loop span is employed by analyzing the coupling relationship between primary and secondary.Then,in order to obtain the secondary flux density,the transient secondary current is solved based on the loop impedance and induced voltage.Finally,the electromagnetic thrust can be calculated reasonably by the given primary current sheet and the calculated secondary flux density.Comprehensive simulations and experiments have demonstrated the effectiveness of the proposed method.

A Convolutional Autoencoder Based Fault Detection Method for Metro Railway Turnout

Railway turnout is one of the critical equipment of Switch&Crossing(S&C)Systems in railway,related to the train’s safety and operation efficiency.With the advancement of intelligent sensors,data-driven fault detection technology for railway turnout has become an important research topic.However,little research in the literature has investigated the capability of data-driven fault detection technology for metro railway turnout.This paper presents a convolutional autoencoder-based fault detection method for the metro railway turnout considering human field inspection scenarios.First,the one-dimensional original time-series signal is converted into a twodimensional image by data pre-processing and 2D representation.Next,a binary classification model based on the convolutional autoencoder is developed to implement fault detection.The profile and structure information can be captured by processing data as images.The performance of our method is evaluated and tested on real-world operational current data in themetro stations.Experimental results show that the proposedmethod achieves better performance,especially in terms of error rate and specificity,and is robust in practical engineering applications.

Research on the cooperative train control method in the metro system for energy saving

Purpose–To address the problem that the current train operation mode that train selects one of several offline pre-generated control schemes before the departure and operates following the scheme after the departure,energy-saving performance of the whole metro system cannot be guaranteed.Design/methodology/approach–A cooperative train control framework is formulated to regulate a novel train operation mode.The classic train four-phase control strategy is improved for generating specific energy-efficient control schemes for each train.An improved brute force(BF)algorithm with a two-layer searching idea is designed to solve the optimisation model of energy-efficient train control schemes.Findings–Case studies on the actual metro line in Guangzhou,China verify the effectiveness of the proposed train control methods compared with four-phase control strategy under different kinds of train operation scenarios and calculation parameters.The verification on the computation efficiency as well as accuracy of the proposed algorithm indicates that it meets the requirement of online optimisation.Originality/value–Most existing studies optimised energy-efficient train timetable or train control strategies through an offline process,which has a defect in coping with the disturbance or delays effectively and promptly during real-time train operation.This paper studies an online optimisation of cooperative train control based on the rolling optimisation idea,where energy-efficient train operation can be realised once train running time is determined,thus mitigating the impact of unpredictable operation situations on the energy-saving performance of trains.

Translation of Metro Station Names in Guangzhou and Foshan from the Perspective of Symbolic Function of Translation Landscape

Guangzhou and Foshan enjoy relatively mature metro network.However,some names of metro stations are over-transliterated in Pinyin.Such a translation method is used in translating general names,nouns of locality and some names of tourist destinations.With translation landscape and linguistic landscape theories,the reasons and impacts of over-transliteration in Guangzhou and Foshan metro will be discussed from the perspective of symbolic function.English names of Metro stations in other cities serve as a reference so as to appropriate solutions.

欧盟质量型选择性分销协议适用Metro标准合理规则的困境——以限制网络销售为例

纵向限制是近年来欧洲竞争法中争议较大的领域,本文探究纵向限制中质量型选择性分销协议的合法性认定标准。在欧盟的纵向限制规制框架下,首先考虑质量型选择性分销协议是否属于《欧盟运行条约》第101条第1款的范围,因此需判断协议的目的或效果是否影响竞争。若协议为该款所规制的对象,那么就要以Metro标准评估选择性分销造成的品牌内竞争减弱是否能被品牌间质量竞争产生的积极效果所抵消。可是Metro标准固然为质量型选择性分销协议提供了合法性认定标准,但是在实际判定过程中存在模糊性,尤其是对合理规则进行具体解释的时候,许多现实问题有待解决。

Last train timetable optimization for metro network to maximize the passenger accessibility over the end-of-service period

Purpose-This study aims to improve the passenger accessibility of passenger demands in the end-ofoperation period.Design/methodology/approach-A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway,the minimum headway and the latest end-of-operation time.The objective of the model is to maximize the number of reachable passengers in the end-of-operation period.A solution method based on a preset train service is proposed,which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.Findings-The results of the case study of Wuhan Metro show that the solution method can obtain highquality solutions in a shorter time;and the shorter the time interval of passenger flow data,the more obvious the advantage of solution speed;after optimization,the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.Originality/value-Existing research results only consider the passengers who take the last train.Compared with previous research,considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination.Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network,but due to the decrease in passenger demand,postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.

时速120 km地铁快线空气动力学试验研究

为探明设计时速120 km快速地铁列车在多区段桥隧衔接线路运行时的气动效应和气密性能,采用实车试验的方法,在武汉某多区段桥隧衔接地铁快线对某4车编组的新研A型密封性地铁列车开展空气动力学测试。实验测试系统采用LL-250-15A型Kulite压力传感器,通过测量列车外部和内部的瞬态压力变化,分析全线路车外压力波动特性,对比沿列车长度方向不同测点位置的压力变化幅值,并分析不同空调状态下的车内压力舒适性。经过3次实验测试分析,该实验的结果具有可重复性。研究结果表明:全线路运行时,列车在隧道段内加减速导致车外压力变化幅值明显大于高架段,气动效应最恶劣的位置为地下段人防门变截面处,列车上行通过该处时车外任意3 s内压力变化幅值为1 071 Pa,下行通过该处时车外任意3 s内压力变化幅值为905 Pa;相对于下行线全线路,上行线车外任意3 s内压力变化幅值大18.3%;列车正线运营时压力波保护阀会在压力变化剧烈区段进行动作响应,列车上行时,空调开启、压力波保护阀正常启用状态下,车内任意3 s内压力变化幅值相对于压力波保护阀打开未启用时减少了16%,下行时,减少了28%,空调压力波保护阀能够有效降低车外压力波动对车内气压变化的影响。本文研究成果可为快速地铁线路设计、地铁列车运营及地铁气密性优化提供参考依据。

地铁列车刨削式防爬吸能结构冲击力平稳行为参数优化

为提升地铁列车在碰撞过程的平稳性和耐撞性,提出一种刨削式吸能防爬器。该吸能结构因其抗偏载能力强,结构紧凑等优点被广泛应用于地铁列车的端部吸能结构中。以某型地铁列车的刨削式防爬器为研究对象,使用有限元仿真的方式建立该吸能结构的对称简化模型,并结合台车冲击的试验数据验证有限元模型的准确性;通过数值仿真的方式,将刨刀前角(α)、刨刀后角(β)、刨刀宽度(w)和刨削深度(d)作为输入变量,以总吸能量(E_(A))和吸能阶段的平均刨削力(M_(PF))为耐撞性指标,以样本方差(S^(2))作为考核参照,通过全因子法对输入变量进行参数化分析;在此基础上,利用径向基函数构建代理模型,并采用多目标遗传算法(MOGA)对该吸能结构的主要设计参数进行优化设计,以确定结构参数的最佳的配置方案。研究结果表明:在该型刨削式防爬吸能结构的主要设计尺寸参数中,β对E_(A)、M_(PF)以及S^(2)的影响均不明显;α对MPF、E_(A)呈负相关,同时与S^(2)呈正相关;w和d对E_(A)与M_(PF)呈正相关、与S^(2)呈负相关;通过优化设计得到的吸能结构的最优的参数设计方案中:d为3.94 mm;α为7.78°,w为34 mm;最优设计方案的E_(A)提高了5.91%,M_(PF)提高了5.89%,S^(2)降低了45.4%,耐撞性与平稳性得到了提高。研究结果可为地铁列车刨削式防爬吸能结构的设计提供工程参考。

公铁合建双层盾构隧道设计关键技术

为解决公铁合建双层盾构隧道面临的总体布置、结构设计、汽车与地铁车辆联合振动以及通风排烟等技术难题,以武汉长江公铁隧道和济南黄河济泺路隧道工程实践为基础,采用方案综合比选、2.5维数值计算等方法,对公铁合建双层盾构隧道设计关键技术进行系统研究。结果表明:1)通过对隧道平面、纵断面和横断面的合理优化布置,并在废水泵房段、疏散楼梯段采取特殊布置方案,可减少公铁合建盾构隧道地下空间占用,并提高断面利用率,减小盾构隧道外径;2)采用半预制半现浇的管片+非封闭内衬结构型式,能充分发挥内部结构与管片衬砌的联合承载作用,显著减小河床冲淤作用;3)汽车与地铁联合振动作用对隧道影响较小,隧道基底饱和粉细砂地层不会发生液化;4)地铁隧道采用分段纵向烟道,可解决地铁长大区间无风井条件下的排烟难题,同时提高疏散便捷性,并大幅降低建设难度;5)公铁合建隧道在运营管理上不可避免地会出现交叉和影响,建议在管理界面划分和投资分劈上提前研究,便于决策。

站台门与钢轨等电位连接方式下的绝缘防护测试及保障措施

[目的]站台门系统与钢轨等电位连接方式下,当站台门系统的对地绝缘降低时,容易产生放电现象。为确保乘客的乘坐安全,应基于该方式,建立有效的站台门绝缘保障措施。[方法]从站台门电气绝缘机理和人体电气安全2个维度分析了站台门与钢轨等电位连接的优势。建立了轨电位计算模型,对常规工况、极端工况2种工况下站台门处轨电位进行了仿真。采用多参数单一变化法,分析了常规工况下各回流系统参数不同取值对站台门轨电位的影响,计算了极端工况下的站台门轨电位分布曲线。提出了站台门绝缘的测试方法及站台门绝缘维护的相关措施。[结果及结论]采用站台门系统与钢轨等电位连接方式时,轨电位的最大值不应超过60 V。极端工况下,站台门处轨电位有可能高于该阈值,此时乘客的人身安全可能会受到威胁,须采取有效措施,确保站台门的绝缘有效性。

北京地铁薄壁地下连续墙基坑变形规律统计分析

[目的]地下连续墙(以下简称“地连墙”)厚度对基坑变形量与变形模式的影响较为明显,尤其是薄壁地连墙对于基坑开挖和坑边荷载十分敏感。因此,有必要对北京地铁不同壁厚的地连墙基坑变形规律进行研究。[方法]以北京地铁6座薄壁地连墙车站基坑工程为例,使用统计学方法对其地面竖向变形、地连墙墙顶竖向变形、地连墙水平位移及钢支撑轴力的监测数据进行统计分析。[结果及结论]薄壁地连墙基坑的地面变形可分为隆起-沉降型和沉降型两种,且地面变形中隆起变形的占比较高。土方开挖阶段,地连墙呈快速隆起趋势,开挖结束后墙顶隆起值产生小幅回落,并最终达到稳定值。根据地连墙变形特征,将其分为正常抛物线型、荷载抛物线A型、荷载抛物线B型3种类型。地连墙最大变形位置一般处于0.50H~0.85H(H为基坑深度),累计变形量集中于10~20 mm。第1道钢支撑轴力变化特征较为明显,其曲线可分为快速上升、快速下降、缓慢下降、快速上升4个阶段。

隧道轮廓激光雷达点云线特征共面约束标定方法

地铁隧道断面轮廓参数测量过程中,需要对高速激光雷达点云进行高精度系统标定。特别是大场景隧道环境,对标定模板要求高,标定过程复杂,检测精度影响大。针对此问题,本论文提出了一种新颖的适用于地铁隧道轮廓点云的标定方法,并基于双激光雷达测量系统,进行了算法研究。本方法设计了专用的手推行便携式标定系统,利用由点云数据提取的标定板线特征,建立目标函数,通过混合了遗传算法和Levenberg-Marquardt算法的非线性优化方法,寻找全局最优解从而实现对激光雷达的标定。实验结果表明:本方法对于两侧钢轨顶轨的标定误差在±1.5 mm以内;静态测量精度X误差在±1 mm内、Y误差在±4 mm内;当采集系统以5 km/h的速度进行数据采集时,动态测量精度X误差在±4 mm内、Y误差在±6 mm内。本方法能够实现激光雷达的高精度标定,算法鲁棒性强,具有易操作、环境适应性强的特点。

基于隐式参数化模型的地铁车体轻量化设计

为实现地铁新车型前期快速的概念设计和性能评估,引用“分析驱动设计”理念对重庆6号线地铁的MP车体进行了隐式参数化建模;并录入车体的17个主要钣金件进行设计分析。以板厚为设计变量,筛选出模态和刚度对质量相对灵敏度较大的7个车体钣金件,进行基于响应面法的多目标轻量化优化设计;车体的刚度、模态等多项性能指标达到了良好的轻量化效果。研究结果表明:所引入“分析驱动设计”理念的车体隐式参数化建模及基于响应面法的多目标优化方法能应用于车体结构的轻量化设计,具有较好的工程指导意义。

新型公共文化空间融合发展:上海地铁“第二空间”建设及启示

为探讨新型公共文化空间融合发展特征,为未来多场景下类似项目建设提供参考与借鉴,文章基于新型阅读空间建设原则,以上海地铁“第二空间”发展阶段为案例进行研究,归纳上海地铁得以建成新型公共文化空间、实现融合发展的内在机理。研究发现,新型公共文化空间融合发展需遵循公共性、创意性、融合性原则,并依赖于城市政府、文化机构、社会民众以及场景责任主体多方协同共建。

空间异质下地铁建成环境与站点覆盖客流吸引度关系研究

机器学习模型广泛应用于探究建成环境与客流的交互关系。然而,机器学习考虑的是全局关系,无法捕捉空间变化,为解决这一问题,本文从密度、多样性、设计、目的地可达性、可获得性和网络连通性等方面构建了11种建成环境指标,提出一种轻量级梯度提升机(LightGBM)与地理加权回归(GWR)的集成综合分析模型(SLightGBM),以探究建成环境对站点覆盖客流吸引度的空间异质性和非线性影响,并将该模型与LightGBM,普通最小二乘法(OLS)和GWR进行比较,以揭示SLightGBM模型在回归效果上的优势。针对西安市的研究结果表明:SLightGBM模型的R2、MAE与RMSE分别达到了0.68、8379.16和11797.19,显著优于对比模型;建成环境因素存在空间异质性,工作人口密度和公交站点密度在中心区域最为重要,而餐饮密度在南部区域更显著;工作人口密度和餐饮密度与客流吸引度呈正相关,而最小换乘次数与客流吸引度呈负相关关系,且具有明显的协同作用。研究表明,影响因子空间差异性和阈值分析结果对于指导城市建设和改善公共交通系统具有重要的启示意义。

基于灰色神经网络的地铁牵引用电预测模型

[目的]为了提高列车运行效率,需对地铁牵引能耗进行监测,并建立相关能耗模型对地铁牵引能耗进行预测分析。[方法]介绍了灰色预测模型和BP(反向传播)神经网络的基本原理;以天津某典型地铁车站2021年6月的牵引日用电量数据为例,采用灰色关联分析法筛选出与地铁牵引日用电量关联度大的影响因素,基于GM(1,1)灰色预测模型预测出短期牵引日用电量;将所筛选出的关联度大的影响因素、GM(1,1)灰色预测模型预测的短期牵引日用电量及相邻历史牵引日用电量数据,作为BP神经网络模型中的输入量进行训练,建立GM-BP灰色神经网络模型,并生成所需短期地铁牵引日用电量预测数据。[结果及结论]与传统GM(1,1)灰色预测模型和BP神经网络模型相比,通过GM-BP灰色神经网络模型预测的短期牵引日用电量预测误差有明显的改善,能够作为有效的地铁牵引能耗数据进行短期预测数据分析。

地铁车站BIM模型信息完备性审查研究

随着智能建造的发展,三维正向设计逐渐替代了传统二维设计,对设计成果的交付审查也将同步转换为对建筑信息模型的审查。地铁建筑设计区别于其他建筑具备较强的功能性,在实际设计交付成果审查中,会存在错审率、漏项高等问题。为解决该问题,本文依据相关国家标准,构建适用于地铁车站建筑信息模型完备性审查的本体模型,同时集成工业基础类(IFC 4.0)实例信息、计算机规则技术,实现模型完备性审查。以地铁车站的建筑单元为例,实现地铁车站模型在方案设计阶段的交付工作。该方法的提出有助于促进整个建筑行业的信息化发展。