Urban Train Research Articles

Experimental investigations on the performance of anti-snow designs for urban rail train bogies

Under weather conditions such as snow and icing in cold regions, snow and ice accumulation on bogies severely affect the running safety and increase the energy consumption of urban rail trains. To analyze the snow and ice accumulation process, experiments for real urban rail train non-powered bogie were conducted for the first time in the Central South University Icing and Snowing Wind Tunnel (CSU-ISWT). Two anti-snow structures (deflectors and wheelset snow shields) with low energy consumption were designed and discussed based on comparative experiments. The following data were collected after each experiment: dynamic accumulation process, final distribution of snow and ice, and total accumulation mass on the bogie. The results showed that the distributions on the original and optimized bogies were similar. Much more snow and ice accumulated on the lower part of the bogie than on the upper part and covered more on the windward side of the frame than on the leeward side. In the experiments with anti-snow structures, the snow and ice mass accumulated on the bogies decreased by 53.35% and 52.64% in the deflectors and wheelset snow shields cases, respectively. The proposed structures were proven to significantly improve anti-snow performance on the bogies. Therefore, the presented initial research can remarkably strengthen the transportation capacity and safety of urban rail trains in winter.

Following Consistency of Energy‐Saving Operation for Urban Rail Trains Based on Event Triggering Mechanism

To reduce the traction energy consumption of urban rail trains by regenerating energy, a train traction and braking model was designed based on algebraic graph theory and train dynamics theory and the following consistency model of energy‐saving operation of urban rail trains was constructed based on the conditions of the coordination coefficient and the operating condition conversion of trains. Not only to constantly update the consistency controller and save communication resources but also to optimize the energy‐saving effect, the consistency algorithm of event triggering was used to search for the optimal operating conditions of trains and the energy‐saving operation scheme for multiple trains was established. Taking the train diagram of a subway line in Jinan as an example, the energy‐saving control scheme of four trains was solved by MATLAB simulation. The simulation results show that the model can not only ensure parking accuracy and punctuality but also energy savings effectively; that is, the proportion of the total regenerative energy used by the follower train in the actual energy consumption is increased from 3.32% to 10.76%, and the actual total energy consumption of the train is reduced by 9.23%.

Adaptive Sliding Mode Control Method for Onboard Supercapacitors System

Urban rail trains have undergone rapid development in recent years due to their punctuality, high capacity and energy efficiency. Urban trains require frequent start/stop operations and are, therefore, prone to high energy losses. As trains have high inertia, the energy that can be recovered from braking comes in short bursts of high power. To effectively recover such braking energy, an onboard supercapacitor system based on a radial basis function neural network-based sliding mode control system is proposed, which provides robust adaptive performance. The supercapacitor energy storage system is connected to a bidirectional DC/DC converter to provide traction energy or absorb regenerative braking energy. In the Boost and Buck modes, the state-space averaging method is used to establish a model and perform exact linearization. An adaptive sliding mode controller is designed, and simulation results show that it can effectively solve the problems of low energy utilization and large voltage fluctuations in urban rail electricity grids, and maximise the recovery and utilization of regenerative braking energy.

Application of quantum-behaved characteristic particle swarm optimization algorithm in multi-objective optimization of urban rail train

Application of quantum-behaved characteristic particle swarm optimization algorithm in multi-objective optimization of urban rail train

Application of quantum-behaved characteristic particle swarm optimisation algorithm in multi-objective optimisation of urban rail train

This paper combines operation control strategy and operation curve to address the problems of frequent switching and high energy consumption of traditional ATO control policies. Firstly, based on the Pareto principle, the objective optimisation model is established based on urban rail trains' punctuality and energy consumption. Then, a multi-objective quantum particle swarm optimisation (MOQPSO) algorithm with fewer control parameters is adopted. The Gaussian mutation operator and crowding distance sorting method are introduced to select the global optimal guidance particles better, and the optimisation effect of the conventional MOPSO algorithm is compared. Finally, the actual data of the Beijing Subway Yizhuang Line are used to verify the algorithm. Simulation results show that the MOQPSO algorithm has advantages in convergence, diversity, and optimisation. At the same time, different control strategies are compared, and the results show that the improved hybrid control strategy has a better optimisation effect on the longer line.

Model of a Composite Energy Storage System for Urban Rail Trains

Model of a Composite Energy Storage System for Urban Rail Trains

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 operating energy utilization rate of trains, a multi-objective particle swarm optimization (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 satisfactory 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 suggested to overcome the shortcomings of the existing algorithms. These methods significantly increase the computational complexity and convergence of the algorithm. An adaptive fuzzy logic system that can simultaneously utilize experience information and field 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.

Urban Rail Transit Network Train Timetable Optimization Considering Cross-Line Operation

Urban Rail Transit Network Train Timetable Optimization Considering Cross-Line Operation

Exploring the Risky Travel Area and Behavior of Car-hailing Service

Recent years have witnessed the rapid development of car-hailing services, which provide a convenient approach for connecting passengers and local drivers using their personal vehicles. At the same time, the concern on passenger safety has gradually emerged and attracted more and more attention. While car-hailing service providers have made considerable efforts on developing real-time trajectory tracking systems and alarm mechanisms, most of them only focus on providing rescue-supporting information rather than preventing potential crimes. Recently, the newly available large-scale car-hailing order data have provided an unparalleled chance for researchers to explore the risky travel area and behavior of car-hailing services, which can be used for building an intelligent crime early warning system. To this end, in this article, we propose a Risky Area and Risky Behavior Evaluation System (RARBEs) based on the real-world car-hailing order data. In RARBEs, we first mine massive multi-source urban data and train an effective area risk prediction model, which estimates area risk at the urban block level. Then, we propose a transverse and longitudinal double detection method, which estimates behavior risk based on two aspects, including fraud trajectory recognition and fraud patterns mining. In particular, we creatively propose a bipartite graph-based algorithm to model the implicit relationship between areas and behaviors, which collaboratively adjusts area risk and behavior risk estimation based on random walk regularization. Finally, extensive experiments on multi-source real-world urban data clearly validate the effectiveness and efficiency of our system.

Effects of mento-physical exercises on mental fatigue of shift work

Objectives. This study aims to investigate whether mento-physical exercises can decrease mental fatigue during shift work. Methods. Research subjects including the control room staff of an urban train system were chosen randomly, for whom mental fatigue was assessed before and after rest breaks for control and experimental groups. A new protocol was applied in the experimental group, including breathing exercises, isometric and isotonic exercises, and progressive relaxation during the inter-shift break. A designed questionnaire and the Stroop test were used to evaluate fatigue and the reaction time, respectively. Results. Pre and post-test results showed that mental, visual and physical fatigue and reaction time decreased by 14.48, 49.22, 26.85 and 8.35% in the control group and 36.42, 48.48, 76.37 and 20.56% in the experimental group, respectively. Conclusions. At the 5% α level, Student’s t test showed that mento-physical exercises effectively decreased mental and physical fatigue as well as reaction time in the experimental group compared to the control group.

Potensi Pengembangan Kawasan Berbasis Transit Oriented Development di Sekitar Titik Transit Kabupaten Bogor

The high number of commuters in Bogor Regency has triggered the development of settlements at transit areas. In addition, Bogor Regency is also connected to rail-based mass public transportation in the Jabodetabek area which supports the mobility of its population. This study aims to identify the suitability of a transit area to be developed with Transit Oriented Development (TOD) concept. The research location is among the transit areas of two intercity train stations and seven existing urban commuter line train stations in Bogor Regency. Observations focused on the area in a radius of 800 meters from the station which is assessed as the maximum distance a person can walk for 15 minutes. Potential locations are determined by the AHP (Analytical Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method on several variables that form the ideal TOD. The variables observed include aspects of transportation and aspects of land use which are derived into several indicators. Based on the research, it was found that the most potential area to be developed with the TOD concept is the transit area of Cibinong station, followed by transit areas of Bojonggede station, Citayam station, and Cilebut station. Meanwhile, transit areas of Parung Panjang station and Tenjo station have medium potential, and transit areas Maseng Station and Cigombong Station are not potential.

Foreign Body Detection in the Electrified Area of Urban Rail Trains Using Improved Yolov3 Algorithm

Foreign body invade the electric receiving area of urban rail train, interfere with the operation of electric equipment on the roof, and affect the normal operation of urban rail traffic. Aiming at the problems of the traditional non-contact foreign body detection in the electric area of urban rail train, such as slow detection speed and poor detection accuracy of small target foreign body, An improved YOLOV3 (You Only Look Once) network model based on PAN feature pyramid structure and adaptive spatial feature fusion is proposed. By improving the main body of the YOLOv3 network model, it can alleviate the problem that the network prediction size map is too large and the experience field is too small. The features of different levels of foreign objects are initially fused with PAN’s feature pyramid to extract strong location information and strong semantic information of the foreign objects, then the method of adaptive spatial feature fusion was used to learn the spatial weights of the fusion of feature maps at various scales, obtaining more effective prediction feature maps at different scales after fusion and improving the detection ability of small targets. The improved k-means clustering algorithm is used to obtain the size of anchor and match it to the corresponding feature layer, which can mark the position of foreign body more accurately. Experimental results show that the detection accuracy of the improved YOLOV3 reaches 95.7%, which is 5.1% higher than the detection effect of the original network. It can accurately and quickly identify the different size of intrusive foreign body in the electric area of the roof of the urban rail train.

Gauss pseudospectral‐based velocity optimization for rail transit trains with running and computation delays

AbstractWith the progress of urban intelligent construction, urban rail transit trains have become one of the most important ways for urban traffic. Optimization operation is a key to further improve the performance of urban rail transit. In this work, an energy saving velocity planning algorithm for rail transit train with running and computation delays is proposed. First, an optimization model with considering both running and computation delays is established for velocity planning. Then, the velocity planning algorithm frame is proposed based on Gauss pseudospectral distribution, where the running delay and computation delay are tackled separately. Meanwhile, the gradient information of transform nonlinear programming (NLP) problem is derived in detail so that NLP solver can be employed to obtain accuracy results. Furthermore, the implementation steps of the proposed algorithm are given. Finally, simulation tests are carried out on a two‐station running rail transit train model with three different delay situations and two different slopes railway. Numerical results and comparison show the effectiveness and correctness of the proposed method for rail transit train velocity planning with delays.

Dynamics of runoff quality associated with an urban park and WSUD treatment train in a tropical climate

ABSTRACT A combination of discrete sampling using autosamplers triggered by area-velocity metres and continuous water quality monitoring using YSI datasondes enabled us to evaluate the dynamics of both stormwater runoff and dry weather water quality associated with an urban park and WSUD treatment train in Singapore. The WSUD treatment train consisted of a raingarden and sedimentation ponds. A first flush phenomenon was observed for total suspended solids (TSS) in three of four discrete-sampled events, but there was a less pronounced first flush characteristic for nutrients. Mean TN concentrations associated with runoff from the park (upstream of the WSUD treatment train) were in the range that would be associated with eutrophic conditions, while mean TP levels were in the mesotrophic/eutrophic boundary range. The raingarden reduced nutrient and TSS levels by 7–62% and loads by 65–93%, although nitrate levels were higher in the effluent compared to the influent. The sedimentation ponds successfully reduced sediment levels by 56%, based on continuous turbidity measurements. The dissolved oxygen levels in the sedimentation ponds were lower during drought periods, which has implications for aquatic organisms. The WSUD treatment train generally improved runoff quality from the park and such features can be easily integrated into the park design.

Fully Automatic Operation Algorithm of Urban Rail Train Based on RBFNN Position Output Constrained Robust Adaptive Control

High parking accuracy, comfort and stability, and fast response speed are important indicators to measure the control performance of a fully automatic operation system. In this paper, aiming at the problem of low accuracy of the fully automatic operation control of urban rail trains, a radial basis function neural network position output-constrained robust adaptive control algorithm based on train operation curve tracking is proposed. Firstly, on the basis of the mechanism of motion mechanics, the nonlinear dynamic model of train motion is established. Then, RBFNN is used to adaptively approximate and compensate for the additional resistance and unknown interference of the train model, and the basic resistance parameter adaptive mechanism is introduced to enhance the anti-interference ability and adaptability of the control system. Lastly, on the basis of the RBFNN position output-constrained robust adaptive control technology, the train can track the desired operation curve, thereby achieving the smooth operation between stations and accurate stopping. The simulation results show that the position output-constrained robust adaptive control algorithm based on RBFNN has good robustness and adaptability. In the case of system parameter uncertainty and external disturbance, the control system can ensure high-precision control and improve the ride comfort.

Dashboard for analyzing SCADA data log: a case study of urban railway in Malaysia

<p>The operation of maintenance in the railway industry is high priorities for safety which reflects the train services. The Kelana Jaya Line (KJL) is the leading urban metro train operator among light rail transit (LRT) categories in Malaysia. The main issue in KJL, they are facing huge historical data from the supervisory control and data acquisition (SCADA) logger when organizing the corrective maintenance work schedule. The previous conventional method leads to time constraint which causes redundancy of data reading. Hence, SCADA Dashboard was developed as a tool to structure their work prioritization for weekly planning. It was developed by using Microsoft Power Query and Power Pivot, in the advanced Excel software. The dashboard evaluation was performed based on usability and user experience studies. The evaluation test proves that the dashboard can be used effectively and it’s beneficial to the organizations as well as a contribution towards systematic maintenance.</p>

Optimization of Urban Rail Automatic Train Operation System Based on RBF Neural Network Adaptive Terminal Sliding Mode Fault Tolerant Control

Aiming at the problem of the large tracking error of the desired curve for the automatic train operation (ATO) control strategy, an ATO control algorithm based on RBF neural network adaptive terminal sliding mode fault-tolerant control (ATSM-FTC-RBFNN) is proposed to realize the accurate tracking control of train operation curve. On the one hand, considering the state delay of trains in operation, a nonlinear dynamic model is established based on the mechanism of motion mechanics. Then, the terminal sliding mode control principle is used to design the ATO control algorithm, and the adaptive mechanism is introduced to enhance the adaptability of the system. On the other hand, RBFNN is used to adaptively approximate and compensate the additional resistance disturbance to the model so that ATO control with larger disturbance can be realized with smaller switching gain, and the tracking performance and anti-interference ability of the system can be enhanced. Finally, considering the actuator failure and the control input limitation, the fault-tolerant mechanism is introduced to further enhance the fault-tolerant performance of the system. The simulation results show that the control can compensate and process the nonlinear effects of control input saturation, delay, and actuator faults synchronously under the condition of uncertain parameters, external disturbances of the system model and can achieve a small error tracking the desired curve.

Optimal size selection for fuel cell and battery in a hybrid power system of the intercity locomotives

An urban train powered by a hybrid power system is studied in this paper in terms of optimization of component size to minimize the overall cost. The hybrid power system consists of a proton exchange membrane fuel cell, a Li-ion battery, and an electric motor. Because of decreasing cost of power generation and urge to use renewable energy sources, utilization of fuel cell in urban train has attracted lots of attention. Using a battery in addition to the fuel cell can mitigate the slow response of the fuel cell when fast increase in power generation is required. The optimum sizes of the battery and fuel cell are determined considering numerous system limits and lifespan of the components. In addition, different track slopes are taken into account when calculating the optimum sizes. To solve the optimization problem, a novel technique named modified student psychology optimization is introduced and utilized. The train movement is studied in slope of 0%, 1%, and 2% to include the possible scenarios of train movement. To compare the performance of the proposed method, the system is optimized by three other optimization methods as well. Comparing the simulations’ results show that the proposed optimization method can decrease the costs by 6.61% on average for the slopes compared to the best comparison method.

Regenerative braking energy recuperation from urban electrified train operation by active rectifier

With a large capacity, the total energy consumption for electrified train operation of the urban railway system is very high. Therefore, energy-saving solutions are very meaningful to retain their outstanding advantages compared to other means of transportation. Recovering regenerative braking energy is the potential solution to improve energy efficiency. This paper proposes a solution to recover regenerative braking energy by an active rectifier installed at a traction substation capable of bi-directional energy flow. In the braking phase, the motor operates as a generator that returns energy to the utility source. Thanks to the active rectifier, regenerative braking energy will be returned to the source without being burned on the braking resistors. The energy efficiency of this solution is verified by simulation results on Matlab Simulink software with simulation data collected from Cat Linh-Ha Dong urban railway, Vietnam. Evaluating the level of energy savings in the cases with/without active rectifiers showed that using the active rectifier had saved 4.4% of the total traction electric energy.

Public Norms in the Operation Scheme of Urban Rail Transit Express Trains: The Case of the Beijing Changping Line

The development of urban rail transit is of great significance to the sustainable development of cities. However, the formulation of public norms of the urban rail transit train operation scheme lacks the corresponding theoretical support, rationality and scientificity. Therefore, based on the research on passenger flow conditions, this paper establishes an optimization model of express train operation and uses a heuristic genetic algorithm to solve it. In addition, this paper takes the Beijing Changping Line as an example to conduct empirical research. Results show that the optimization model established reduces the operation cost of operating enterprises, improves the capacity of urban rail transit, reduces travel time and maintains the full load rate of trains at a more comfortable level. This will improve the attractiveness of urban rail transit and promote benign interaction between operators and passengers. It will also provide a theoretical basis for formulating public norms of transit train operation, make it more scientific and reasonable and promote the development of urban rail transit.