Predictive Control Algorithm for Urban Rail Train Brake Control System Based on T-S Fuzzy Model

Urban rail transit has the advantages of large traffic capacity,high punctuality and zero congestion,and it plays an increasingly important role in modern urban life.Braking system is an important system of urban rail train,which directly affects the performance and safety of train operation and impacts passenger comfort.The braking performance of urban rail trains is directly related to the improvement of train speed and transportation capacity.Also,urban rail transit has the characteristics of high speed,short station distance,frequent starting,and frequent braking.This makes the braking control system constitute a time-varying,time-delaying and nonlinear control system,especially the braking force changes directly disturb the parking accuracy and comfort.To solve these issues,a predictive control algorithm based on T-S fuzzy model was proposed and applied to the train braking control system.Compared with the traditional PID control algorithm and self-adaptive fuzzy PID control algorithm,the braking capacity of urban rail train was improved by 8%.The algorithm can achieve fast and accurate synchronous braking,thereby overcoming the dynamic influence of the uncertainty,hysteresis and time-varying factors of the controlled object.Finally,the desired control objectives can be achieved,the system will have superior robustness,stability and comfort.

Automatic Driving Operation Strategy of Urban Rail Train Based on Improved DQN Algorithm

To realize a better automatic train driving operation control strategy for urban rail trains,an automatic train driving method with improved DQN algorithm(classical deep reinforcement learning algorithm)is proposed as a research object.Firstly,the train control model is established by considering the train operation requirements.Secondly,the dueling network and DDQN ideas are introduced to prevent the value function overestimation problem.Finally,the priority experience playback and“restricted speed arrival time”are used to reduce the useless experience utilization.The experiments are carried out to verify the train operation strategy method by simulating the actual line conditions.From the experimental results,the train operation meets the ATO requirements,the energy consumption is 15.75%more energy-efficient than the actual operation,and the algorithm convergence speed is improved by about 37%.The improved DQN method not only enhances the efficiency of the algorithm but also forms a more effective operation strategy than the actual operation,thereby contributing meaningfully to the advancement of automatic train operation intelligence.

Study on Optimization of Urban Rail Train Operation Control Curve Based on Improved Multi-Objective Genetic Algorithm

A multi-objective improved genetic algorithm is constructed to solve the train operation simulation model of urban rail train and find the optimal operation curve.In the train control system,the conversion point of operating mode is the basic of gene encoding and the chromosome composed of multiple genes represents a control scheme,and the initial population can be formed by the way.The fitness function can be designed by the design requirements of the train control stop error,time error and energy consumption.the effectiveness of new individual can be ensured by checking the validity of the original individual when its in the process of selection,crossover and mutation,and the optimal algorithm will be joined all the operators to make the new group not eliminate on the best individual of the last generation.The simulation result shows that the proposed genetic algorithm comparing with the optimized multi-particle simulation model can reduce more than 10%energy consumption,it can provide a large amount of sub-optimal solution and has obvious optimization effect.

Operation Optimal Control of Urban Rail Train Based on Multi-Objective Particle Swarm Optimization

The energy consumption of train operation occupies a large proportion of the total consumption of railway transportation.In order to improve the oper-ating energy utilization rate of trains,a multi-objective particle swarm optimiza-tion(MPSO)algorithm with energy consumption,punctuality and parking accuracy as the objective and safety as the constraint is built.To accelerate its the convergence process,the train operation progression is divided into several modes according to the train speed-distance curve.A human-computer interactive particle swarm optimization algorithm is proposed,which presents the optimized results after a certain number of iterations to the decision maker,and the satisfac-tory outcomes can be obtained after a limited number of adjustments.The multi-objective particle swarm optimization(MPSO)algorithm is used to optimize the train operation process.An algorithm based on the important relationship between the objective and the preference information of the given reference points is sug-gested to overcome the shortcomings of the existing algorithms.These methods significantly increase the computational complexity and convergence of the algo-rithm.An adaptive fuzzy logic system that can simultaneously utilize experience information andfield data information is proposed to adjust the consequences of off-line optimization in real time,thereby eliminating the influence of uncertainty on train operation.After optimization and adjustment,the whole running time has been increased by 0.5 s,the energy consumption has been reduced by 12%,the parking accuracy has been increased by 8%,and the comprehensive performance has been enhanced.

Optimization of train plan for urban rail transit in the multi-routing mode

The train plan of urban rail transit under multi-routing mode can be divided into three parts： train formation, train operation periods and corresponding train counts of each routing in each period. Based on the analysis of passen- ger＇s general travel expenses and operator＇s benefits, the constraints and objective functions are defined and the multiobjective optimization model for the train plan of urban rail transit is presented. Factors considered in the multi- objective optimization model include transport capacity, the requirements of traffic organization, corporation benefits, passenger demands, and passenger choice behavior under multi-train-routing mode. According to the characteristics of this model and practical planning experience, a three-phase solution was designed to gradually optimize the train formarion, train counts as well as operation periods. The instance of Changsha Metro Line 2 validates the feasibility and efficiency of this approach.

Preliminary Study on Selling Tickets in Reason for Last Trains on Beijing Rail Transit Network

With the increase of Beijing urban rail transport network, the structure of the road network is becoming more complex, and passengers have more travel options. Together with the complex paths and different timetables, taking the last train is becoming much more difficult and unsuccessful. To avoid losses, we propose feasible suggestions to the last train with reasonable selling tickets system.

智能轨道列车动态无线供电系统无源控制研究

互感变化会引起智能轨道列车动态无线供电系统输出功率波动,影响系统的稳定性和可靠性,而传统的线性控制策略动态性能差,不能很好地适应动态无线供电系统。为此,本文基于无源控制理论(PBC)提出了一种适用于智能轨道列车动态无线供电系统的恒功率控制策略。首先,介绍了智能轨道列车DWPT系统结构,建立了系统等效电路模型,分析了传输特性与启动特性,得到了实现系统恒功率输出所需条件。然后,在此基础上,推导出了DC–DC变换器的EL方程,验证了变换器的无源性;基于无源控制理论,通过能量塑造与虚拟阻尼注入设计了无源控制器,并通过控制流入副边DC–DC变换器电流期望值实现系统输出功率恒定。同时,设计了预充回路保护电气设备,利用车载储能设备反向对DC–DC变换器中的储能元件进行预充电,以防止启动瞬间冲击电流过大。在MATLAB/Simulink中搭建相应的仿真模型进行仿真,并搭建300 kW智能轨道列车动态无线供电系统实验平台进行实验。仿真和实验结果表明:相对于传统控制策略,本文提出的PBC策略可使得DWPT系统输出功率不受互感波动的影响,平均功率维持在298.2 kW,且预充回路能抑制启动瞬间的冲击电流,证实了本文所提控制策略的有效性与正确性,具有响应速度快和鲁棒性强等优势。

基于车车通信的列车自主运行系统工程要点设计方案研究

列车自主运行系统(TACS)作为新一代城市轨道交通列控系统,在我国应用仍处于初级阶段,工程实践中存在冗余不足、兼容性差、后备运营模式缺失等问题,难以满足高安全性和高可靠性的运营需求。以深圳地铁20号线信号系统工程为背景,对TACS应用中的无线通信技术方案、后备模式、车辆段列车控制、联络线接口等要点问题进行深入研究,形成可行的工程要点设计方案。研究结果表明:无线通信系统采用LTE-A/B+WLAN方案,可增加无线通信系统的冗余能力;后备模式选用基于列车自主定位的降级运行系统,使系统结构更简单;车辆段非自动化区域纳入列车自动控制(ATC)系统管控范围,运营模式设置为有人驾驶模式,可实现系统加人工双重防护;采用专用接口模块实现联络线接口功能,能够有效解决边界管理问题。研究结果可为TACS的推广应用提供一定技术支撑。

高速列车偏心车轮踏面的高阶多边形磨耗机理研究

目的研究高铁车轮几何偏心与车轮踏面高阶多边形磨耗之间的关系。方法在匀速运行期间对高速列车轴箱体的三向振动加速度进行测试,并分析功率谱密度;建立轮对-钢轨系统有限元模型,采用瞬时动态法计算车轮不同几何偏心工况下轮轨力的波动情况;采用复特征值法分析轮轨在饱和纵向蠕滑力激励下系统的稳定性,预测引起车轮高阶多边形磨耗的轮轨不稳定振动,并研究对列车运行速度和运营环境的影响。结果高速列车以237 km/h的速度运行且轮轨摩擦因数为0.23时,0.7 mm及以上的车轮几何偏心量会导致轮轨最大纵向蠕滑力达到饱和状态,引起614 Hz的轮轨系统不稳定振动,造成车轮24~25阶多边形磨耗的形成。当车速从200 km/h分别增至300、400 km/h时,引起纵向蠕滑力饱和的车轮几何偏心临界值从0.8 mm分别减至约0.67、0.56 mm。当轮轨间摩擦因数为0.21及以上时,饱和纵向蠕滑力激励的轮轨系统614 Hz不稳定振动的等效阻尼比随着轮轨摩擦因数的增大而减小。在摩擦因数0.21~0.27范围内,该振动的发生趋势线性增强。当摩擦因数降至0.21以下时,该振动趋于稳定。结论在列车高速运行时,超过一定临界值的车轮几何偏心可引起轮轨纵向蠕滑力周期性饱和,激发轮轨系统不稳定振动,从而引起踏面高阶多边形磨耗。车速的提高会导致车轮几何偏心临界值的降低,轮轨摩擦因数增大会造成不稳定振动的发生趋势线性增强,进而引发更为严重的车轮高阶多边形磨耗。

Scheduling of high-speed rail traffic based on discrete-time movement model

In this paper, a new simulation approach for solving the mixed train scheduling problem on the high-speed double-track rail line is presented. Based on the discrete-time movement model, we propose control strategies for mixed train movement with different speeds on a high-speed double-track rail line, including braking strategy, priority rule, travelling strategy, and departing rule. A new detailed algorithm is also presented based on the proposed control strategies for mixed train movement. Moreover, we analyze the dynamic properties of rail traffic flow on a high-speed rail line. Using our proposed method, we can effectively simulate the mixed train schedule on a rail line. The numerical results demonstrate that an appropriate decrease of the departure interval can enhance the capacity, and a suitable increase of the distance between two adjacent stations can enhance the average speed. Meanwhile, the capacity and the average speed will be increased by appropriately enhancing the ratio of faster train number to slower train number from 1.

A dynamic simulation of the wheel–rail impact caused by a wheel flat using a 3D rolling contact model

A three-dimensional （3-D） wheel-rail rolling contact model with a wheel fiat was built using commercial software Hypermesh, and the dynamic finite element simulation was conducted using LS-DYNA 3D/explicit code. Influences of the train speed, flat length and axle load on the vertical wheel-rail impact response were discussed, respectively. The results show that the maximum vertical wheel-rail impact force induced by the wheel flat is higher than that generated by the perfect wheel, and these two dynamic impact forces are much greater than the static axle load. Besides, the maximum von Mises equivalent stress and maximum equivalent plastic strain are observed on the wheel-rail contact surface, and both of them as well as the maximum wheel-rail impact force are sensitive to train speed, fiat length and axle load.

面向虚拟连挂的城轨列车群组追踪运行仿真研究

城市轨道交通是解决城市交通拥堵问题最强有效的绿色交通方式,其高峰期客流激增且客流时空分布不均,而面向虚拟连挂的城轨列车动态灵活编组和群组追踪运行能有效满足复杂多变的城轨运营需求。本文剖析面向虚拟连挂的城轨列车群组追踪运行过程,给出虚拟连挂列车群组最小安全追踪距离计算公式;以单列标准车长的线路路段为一个元胞单元,设计速度及位移更新规则,构建基于元胞自动机的城轨列车群组追踪运行仿真模型;以某市地铁2号线为背景,多角度仿真刻画面向虚拟连挂的城轨列车群组追踪运行性能。仿真结果表明:面向虚拟连挂的城轨列车群组追踪运行模型能有效缩短列车最小安全追踪间隔时间,城轨线路通过能力较移动闭塞制式提高78.4%;头车延迟引起的后续列车晚点总数量及总晚点时间更小,呈现出更佳的抗干扰性与恢复性能,且宜采用小编组列车实现虚拟连挂;动态混合编组的城轨列车群组追踪运行性能最佳,单一小编组的次之,大编组列车群宜在小编组列车群前面运行;城轨列车群组旅行速度总体上与平均站间距呈正相关;当列车发车间隔大于延迟时间时,平均站间距对列车群组的延迟影响不敏感,相反,则影响较为显著。研究结论能够为面向虚拟连挂的城轨列车群组追踪运行决策提供技术支撑。

基于Sarsa算法的城轨列车节能控制策略研究

针对城市轨道交通节能运行问题,提出一种基于Sarsa强化学习算法的城轨列车节能控制策略,实现了城轨列车在自动驾驶状态下,面对不同路况,执行减少能源消耗驾驶策略的同时兼顾准时性和舒适性。根据线路条件将列车状态进行离散化处理,将连续的驾驶过程分为若干个子区间进行分段求解。结合区间限速、初始状态、终末状态等限制条件,基于能耗及运行时间分别构造适当的奖励函数。同时,用当前状态下可达的最大速度与最小速度对可选速度集合进行限制,缩小探索空间,加快算法收敛。最后,通过对北京铁路亦庄线小红门站至肖村站的实例进行仿真。实验结果表明,与传统的动态规划方法相比,Sarsa算法在满足舒适性和准时性要求的情况下节能9.32%。相比于强化学习中的Q学习算法,在速度的选取过程中,超速次数也有明显下降。仿真结果证明Sarsa算法具有更好的节能效果和安全性。在算法参数不变的情况下,调整限速条件,与传统动态规划算法进行二次对比,依旧节能4.21%,验证了算法的鲁棒性。

A New Multi-Objective Model to Optimise Rail Transport Scheduler

The sugarcane transport system plays a critical role in the overall performance of Australia’s sugarcane industry. An inefficient sugarcane transport system interrupts the raw sugarcane harvesting process, delays the delivery of sugarcane to the mill, deteriorates the sugar quality, increases the usage of empty bins, and leads to the additional sugarcane production costs. Due to these negative effects, there is an urgent need for an efficient sugarcane transport schedule that should be developed by the rail schedulers. In this study, a multi-objective model using mixed integer programming (MIP) is developed to produce an industry-oriented scheduling optimiser for sugarcane rail transport system. The exact MIP solver (IBM ILOG-CPLEX) is applied to minimise the makespan and the total operating time as multi-objective functions. Moreover, the so-called Siding neighbourhood search (SNS) algorithm is developed and integrated with Sidings Satisfaction Priorities (SSP) and Rail Conflict Elimination (RCE) algorithms to solve the problem in a more efficient way. In implementation, the sugarcane transport system of Kalamia Sugar Mill that is a coastal locality about 1050 km northwest of Brisbane city is investigated as a real case study. Computational experiments indicate that high-quality solutions are obtainable in industry-scale applications.

基于车车通信列控系统的城市轨道交通列车运行效率分析

[目的]城市轨道交通T2T(车车通信)列控系统是一种新型的信号系统,其通过资源化管理方式对轨旁设备进行管控。为了验证该系统的优越性,需对该系统下的列车运行效率进行分析。[方法]针对T2T列控系统,基于资源管理层面和安全防护原理的特点,在折返工况下,将原本由联锁控制的双动道岔转变为两个单动道岔,并基于列车精确自定位实现ATP(列车自动防护),提高了岔区线路资源的使用能力;在区间和车站追踪工况下,通过前后车对于车速、加速度、所处线路位置等信息的实时互传,利用相对速度安全防护原理进一步缩小了列车的追踪间隔。通过上述两方面的技术革新,结合城市轨道交通线路的实际数据,对站后交叉渡线折返、站前单渡线折返、区间与车站追踪等运营场景进行了模拟仿真计算,确定了T2T列控系统的折返能力和区间追踪能力。[结果及结论]相较传统的CBTC(基于通信的列车控制系统),T2T列控系统在折返能力、追踪能力等方面均有着显著提升,更加适应于超大运量的城市轨道交通线路;T2T列控系统架构简单,轨旁设备少,尤其适合城市轨道交通的大修改造项目。

Urban rail departure capacity analysis based on a cellular automaton model

As an important traffic mode, urban rail transit is constantly developing toward improvement in service capacity and quality. When an urban rail transit system is evaluated in terms of its service capacity, the train departure capacity is an important index that can objectively reflect the service level of an urban rail transit facility. In light of the existing cellular automaton models, this paper proposes a suitable cellular automaton model to analyze the train departure capacity of urban rail transit under different variable factors and conditions. The established model can demonstrate the train operating processes by implementing the proposed sound rules, including the rules of train departure at the origin and intermediate stations, and the velocity and position updating rules. The properties of train traffic are analyzed via numerical experiments. The numerical results show that the departure capacity is negatively affected by the train departure control manner. In addition, （i） the real-time signal control can offer a higher train service frequency; （ii） the departure capacity gradually rises with the decrease in the line design speed to a limited extent; （iii） the departure capacity decreases with extension in the train length; （iv） the number of departed trains decreases as the train stop time increases; （v） the departure capacity is not affected by the section length. However, the longer the length, the worse the service quality of the urban rail transit line. The experiments show that the proposed cellular automaton model can be used to analyze the train service capacity of an urban rail transit system by performing quantitative analysis under various considered factors, conditions, and management modes.

Minimum Curve Radii for High-Speed Trains, Including the Gyroscopic Moments of the Wheels

This paper studies the title problem including an analysis of the gyroscopic effects of the wheels of a rail-car travelling at high-speed around a level, horizontal curve. The analysis is based upon the fundamental principles of dynamics. The result is a design formula for the minimum curve radius needed to prevent derailment. Aside from the rail car geometric and physical properties, the minimum curve radius depends upon the square the train speed. An illustrative example shows that the wheel gyroscopic effect is destabilizing and additive to the centrifugal force derailment tendency. From a track design perspective, however, the gyroscopic effect is relatively small compared with the centrifugal force effect.

不同牵引特性城轨列车车轮磨耗与疲劳研究

针对列车频繁牵引起动对车轮磨耗与疲劳损伤产生的影响问题,在恒定牵引力的基础上,探究了不同牵引特性曲线恒功率区转折点速度对车轮磨耗与疲劳的影响规律。采用SIMPACK和MATLAB软件进行联合仿真,建立了不同牵引特性下城轨列车动力学模型和基于Archard的车轮磨耗模型,分析在牵引电机不同起动转矩下牵引特性曲线恒功率区转折点速度对城轨列车轮轨蠕滑率、车轮磨耗深度、磨耗面积以及疲劳指数的影响规律。结果表明:列车牵引起动过程中,电机起动转矩越大,轮轨蠕滑率、车轮磨耗深度和磨耗面积也越大,而疲劳指数则越小;电机起动转矩一定时,随着列车牵引特性曲线恒功率区转折点速度的增大,轮轨蠕滑率、车轮磨耗深度和磨耗面积也增大,疲劳指数则有所减小;当电机起动转矩从800 N·m增大到1400 N·m,车轮磨耗深度和磨耗面积增长率最大为6.9%和12.6%,而疲劳指数下降率最大为7.2%;当恒功率区转折点速度从50 km/h增加到80 km/h,车轮磨耗深度和磨耗面积增长率最大为4.4%和4.3%,疲劳指数下降率最大为1.9%。本文研究了车辆起动转矩与恒功率转折点速度变化对车轮磨耗与疲劳的影响规律,可为车辆牵引特性设计和电机控制以及车轮运维提供参考。

Analysis of torque transmitting behavior and wheel slip prevention control during regenerative braking for high speed EMU trains

The wheel-rail adhesion control for regenerative braking systems of high speed electric multiple unit trains is crucial to maintaining the stability,improving the adhesion utilization,and achieving deep energy recovery.There remain technical challenges mainly because of the nonlinear,uncertain,and varying features of wheel-rail contact conditions.This research analyzes the torque transmitting behavior during regenerative braking,and proposes a novel methodology to detect the wheel-rail adhesion stability.Then,applications to the wheel slip prevention during braking are investigated,and the optimal slip ratio control scheme is proposed,which is based on a novel optimal reference generation of the slip ratio and a robust sliding mode control.The proposed methodology achieves the optimal braking performancewithoutthewheel-railcontactinformation.Numerical simulation results for uncertain slippery rails verify the effectiveness of the proposed methodology.

城轨列车自动驾驶积分反步线性自抗扰控制

针对列车在外部干扰和不确定动态下的速度控制问题,设计了融合积分反步法和线性自抗扰的复合控制方案.首先,考虑列车具有强耦合性,为了更加符合列车真实的纵向动力学特性和受力情况,建立了具有时变系数的多质点模型.其次,为了降低参数调节的难度,跟踪微分器和扩张状态观测器均采用线性形式.跟踪微分器用于求取微分信号,同时具有滤波作用.利用跟踪微分器对虚拟控制量进行求导,正好可解决反步法中存在的“微分爆炸”问题.扩张状态观测器用于实时估计总和扰动.此外,利用积分反步法改进了误差反馈控制律,设计了一种积分反步线性自抗扰控制(IBS-LADRC)算法.最后,证明了观测误差的收敛性及闭环系统稳定性.结合杭州地铁6号线AH型动车组参数和实际线路数据进行仿真,并将IBSLADRC与反步法、线性自抗扰算法、PID控制进行对比,结果表明:IBS-LADRC方法下各动力单元速度误差均处在±0.04 km/h以内,加速度处在±1 m/s2以内,加速度和速度误差均变化较平稳;车钩力相对其他3类方法最小,变化也最平缓,最大车钩力仅为2 320 N;本文控制策略对列车期望速度具有较高的跟踪精度,有利于保证车钩安全,防止车钩断裂,并提高列车运行的安全性、平稳性及乘客舒适度.