Subway Train Research Articles

Preventive maintenance optimization for key components of subway train bogie with consideration of failure risk

With the acceleration of urbanization, the number of urban rail transit trains has increased dramatically, and the economy and safety of subway trains have become important standards. As an essential subsystem of the subway train, the bogie has a long maintenance process and serious failure consequences. So, it is essential to formulate a reasonable maintenance strategy to ensure its operation. To solve the above problems, a preventive maintenance (PM) strategy for key components of train bogie is established with consideration of failure risk in this paper. Firstly, the failure risk factors of the bogie components are scored and weighted, and the failure risk cost model and PM cost model are established. Next, a Weibull distribution parameter estimation method for bogie components based on the improved beluga whale optimization algorithm (IBWO) is proposed, providing a theoretical basis for PM decision-making optimization. Then, the Lévy flight is introduced into particle swarm optimization to enhance the optimization performance of the model and obtain the optimal solution. Finally, the bogie key components of Nanning Metro line 1 are selected as a case study. The results show that the IBWO algorithm has strong applicability and feasibility, and can accurately calculate the Weibull parameter values of the bogie key components. Compared with the PM plan without considering the failure risk, the proposed method is more economical and safer, which can provide necessary theoretical support for the maintenance decision optimization of urban rail transit train components.

Performance Comparison of Traction Synchronous Motors with Ferrite Magnets for a Subway Train: Reluctance versus Homopolar Variants

Due to the high cost and the predicted shortage of rare earth elements in the near future, the task of developing energy-efficient electric machines without rare earth magnets is of great importance. This article presents a comparative analysis of optimized designs of a ferrite-assisted synchronous reluctance machine (FaSynRM) and a ferrite-assisted synchronous homopolar machine (FaSHM) in a 370-kW subway train drive. The objectives of optimizing these traction machines are to reduce their losses, maximum armature current, and torque ripple. The optimization considers the characteristics of the machines in the subway train moving cycle. The problem of the risk of irreversible demagnetization of ferrites in the FaSynRM and FaSHM is also considered. To reduce the computational burden, the Nelder-Mead method is used for the optimization. It is shown that the FaSHM demonstrates better field weakening capability, which can reduce the maximum current, power, and cost of the inverter power modules. At the same time, the FaSynRM requires less permanent magnet mass for the same torque density and is more resistant to irreversible demagnetization, which can reduce costs and improve the reliability of the electric machine.

A simple method for predicting pressure transients in high-speed subway tunnel based on train reflected waves

The aerodynamic pressure transients caused by high-speed subway trains entering the tunnel can usually be simulated with high accuracy using three-dimensional compressible numerical simulation methods. However, these methods often require high computer resources, complex pre-processing and post-processing processes. For practical engineering design, it is difficult to use these methods to achieve fast and simple calculation. In this paper, a train wave signature method (TWS method) proposed by previous scholars in high-speed railroad tunnels was introduced, the principles of the method were explained in detail and a generalized computational method for predicting the pressure time history was established. Additionally, an improved TWS method based on the reflected waves from trains was proposed by analyzing the reflection mechanism of pressure waves encountering trains during the trains passing through the tunnel, and the calculation results were verified by using field measurements and three-dimensional numerical simulations. The results show that the improved TWS method has better accuracy compared to the TWS method. Furthermore, this paper presents a smoothing method to enhance the optimization of the improved TWS method and extends its feasibility for pressure gradient calculation.

Prediction of back-layering length in subway tunnel with on-fire train running

The exploitation and utilization of urban underground space effectively contribute to the sustainable development of society. Tunnel fire safety is necessary to ensure normal operation. Motion train fire is more serious and complex than stationary fire in tunnels due to the influence of unsteady piston wind. This study investigates the smoke back-layering characteristics of a burning subway train during emergency braking. A three-dimensional unsteady numerical model adopting the dynamic mesh technique is built to investigate the smoke diffusion characteristics of motion train fire. Experimental tests are conducted based on a 60 m-long scaled-down experimental setup to verify the accuracy of the numerical model. On this basis, the dynamic characteristics of smoke back-layering length as the longitudinal wind pressure is less than the critical value are studied, considering the influence of heat release rate (HRR), train speed, and train deceleration. The results indicate that the maximum back-layering length follows the logarithmic law with the variation of longitudinal wind pressure. An empirical model is proposed to predict the maximum back-layering length at various longitudinal wind pressure, and it is helpful to the optimization design of ventilation systems for tunnel motion fire.

Event-Triggered Cooperative Model-Free Adaptive Iterative Learning Control for Multiple Subway Trains With Actuator Faults.

This article investigates the issue of speed tracking and dynamic adjustment of headway for the repeatable multiple subway trains (MSTs) system in the case of actuator faults. First, the repeatable nonlinear subway train system is transformed into an iteration-related full-form dynamic linearization (IFFDL) data model. Then, the event-triggered cooperative model-free adaptive iterative learning control (ET-CMFAILC) scheme based on the IFFDL data model for MSTs is designed. The control scheme includes the following four parts: 1) the cooperative control algorithm is derived by the cost function to realize cooperation of MSTs; 2) the radial basis function neural network (RBFNN) algorithm along the iteration axis is constructed to compensate the effects of iteration-time-varying actuator faults; 3) the projection algorithm is employed to estimate unknown complex nonlinear terms; and 4) the asynchronous event-triggered mechanism operated along the time domain and iteration domain is applied to lessen the communication and computational burden. Theoretical analysis and simulation results show that the effectiveness of the proposed ET-CMFAILC scheme, which can ensure that the speed tracking errors of MSTs are bounded and the distances of adjacent subway trains are stabilized in the safe range.

Piston effect of subway trains under different operating conditions and its influence on passenger thermal comfort

With the rapid development of rail transportation, environmental issues of subway become more and more significant, while the thermal comfort of passengers also draws wide attention. There are various arrival conditions for actual subway trains, and their effects on subway stations and passengers have rarely been studied. This paper is the first to investigate the piston effect of subway trains under single and double train arrival conditions and its impact on passenger thermal comfort. Firstly, a transient 3D numerical model based on the real metro station is established. Then, the influencing factors of the piston effect are analyzed, including the maximum travel speed of single train and the different arrival time intervals of two trains. Moreover, inhomogeneity coefficient (Kt and Ku) and the predicted mean vote (PMV) model and the predicted percentage dissatisfaction (PPD) index are introduced to analyze the thermal comfort. The results show that the two-train condition has a more uniform temperature and velocity distribution than the single-train condition. However, the best thermal comfort is obtained for the two arrival conditions of single train traveling at 16.2 m/s and two-train arrival time interval of 1s from the PMV and PPD. Besides, the fresh air volume of the two-train model is increased by 100% than that of the single-train model, which indicates that the double-train model is better than the single-train for station ventilation. These studies provide important theoretical guidance and references for optimizing metro train operation strategies and the design of thermal environments in metro stations.

Detection of SARS-CoV-2 in the indoor air and surfaces of subway trains in Mashhad, Iran.

Millions of passengers around the world are concerned with the possibility of SARS-CoV-2 contamination on public transportation. Therefore, this study aimed to investigate the presence of SARS-CoV-2 virus in indoor air and subway surfaces in Mashhad. In this study, air and surface sampling were done at two times in the morning (7-8:30 a.m.) and evening (3:30-5 p.m.), simultaneously in two wagons for men and women in line 1 of Mashhad Metro in March 2021 to detect the virus and measure the concentration of particulate matter. Totally, 30 air and 30 metro samples were collected and examined by reverse transcriptase-polymerase chain reaction (RT-PCR). The results showed that three and two cases in the air and surface samples were infected with the SARS-CoV-2 virus, respectively. There was a significant relationship between the mean concentration of suspended particles PM1 (particulate matter smaller than 1 μm) with PM2.5 (particulate matter smaller than 2.5 μm) and PM10 (particulate matter smaller than 10 μm) (p < 0. 05). There was also a significant relationship between the mean concentration of suspended particles PM2.5 and PM10. The results showed that the mean PM2.5 measured in the indoor air of the Mashhad metro wagon had a significant relationship with WHO and US EPA and national standards, and its value was higher than the standards (p < 0.05). The average particle concentrations of PM1, PM2.5, and PM10 were equal to 40.46, 42.61, and 48.31 μg/m3. According to the results of the pollution detected in this study, COVID-19 may be transmitted by air and environmental surfaces. Our study emphasizes the need for continuous assessment of the presence of the virus in public transportation. Detection of viral RNA in subways indicates the necessity of adequate disinfection in public settings, strictness in disinfection methods, strengthening of educational activities for sanitary measures, physical spacing plan, and increasing ventilation of wagons.

ESO-Based Model-Free Adaptive Iterative Learning Energy-Efficient Control for Subway Train With Disturbances and Over-Speed Protection

An extended state observer based model-free adaptive iterative learning energy-efficient control (ESO-based MFAILEEC) scheme for subway train speed tracking with external disturbances and over-speed protection under the constraint on traction/braking force is proposed. Firstly, the continuous-time train motion dynamics is formulated into a discrete-time data model with consideration of external disturbances by applying the iterative dynamic linearization. Meanwhile, the external disturbances and the unknown nonlinear uncertainties of the train are transformed into a new state, which is estimated by an ESO designed in the iteration domain. Then, the ESO-based energy-efficient controller with learning ability is designed, which enables the train to achieve the purpose of energy efficiency by reducing the input force. Further, over-speed protection with trigger mechanism is developed to ensure the train operates within safe speed range. All the control strategies are designed under the constraint on traction/braking force by considering the practical limitation of the train system. No model information is involved in the whole design processes and it is a pure data-driven iterative learning approach. Rigorous mathematical analysis proves the feasibility and the robustness of the proposed method, which can guarantee the train operates safely and reliably. Finally, the simulation results further demonstrate the effectiveness of the proposed algorithm.

Acceptability of autonomous trains with different grades of automation by potential users: A qualitative approach

While automation in public transport has gained new momentum in recent decades, the Autonomous Train (AT) is still in its infancy. To guide the deployment of the AT, it is necessary to study its acceptability by the public. The aim of this study was to investigate for the first time the factors that influence the acceptability of the AT. This qualitative study comprised interviews divided into 3 parts. The first part was devoted to free evocation of the AT, while the following ones asked participants to express themselves on the definition of the AT without a driver but with on-board staff (GoA3) and then without any staff on board (GoA4). Thirty participants were interviewed. The sample was balanced in age, gender, train usage, and living location. The semi-structured interviews were recorded, transcribed, and analysed according to the method of thematic content analysis. Overall, the results showed a lack of knowledge and an idealized representation of the AT. Participants expressed several concerns inherent in the deployment of ATs. Lastly, the intention to use was more favourable in GoA3 than in GoA4. In fact, the participants expressed rejection of GoA4, due to the absence of on-board staff and lack of trust in remote communication tools and train supervisors. This article is the first to explore the public acceptability of the AT by adopting an interview methodology to avoid priming participants’ responses. It thus adds to the field of research on the acceptability of autonomous vehicles the railway world which previously focused on driverless subway and freight trains only and now opens the idea of AT on a regular train service.

Optimal Control Algorithm for Subway Train Operation by Proximal Policy Optimization

With the increasing scale of the urban subway, the total energy consumption of the subway has increased dramatically and poses a great challenge to the comfort of passengers and the punctuality of train operation. In order to ensure on-time train operation and passenger comfort, and at the same time reduce the energy consumption of subway operation, this paper proposes a Proximal Policy Optimization (PPO)-based optimization algorithm for the optimal control of subway train operation. Firstly, a reinforcement learning architecture for optimal control of subway train operation is constructed with the position and speed of train operation as the reinforcement learning state, energy consumption and comfort as the optimization objectives, and train operation time as the constraint. The proposed reinforcement learning model is trained by the PPO algorithm, and the reward scaling is added to the training process to accelerate the training speed and improve the efficiency of the algorithm. The experimental results show that the proposed PPO with reward scaling algorithm can effectively reduce train energy consumption and improve passenger comfort while ensuring on-time train operation.

Analysis of the generation mechanism and evolution of the wheel high-order polygonal wear of subway trains

The present paper aims to study the generation cause of initial high-order polygonization of subway wheels as well as its progression pattern. In analyzing the wear characteristics of out-of-round (OOR) wheels of metro trains obtained via field measurements, the distribution of wheel high-order OOR wear was found to be closely related to the small-radius (i.e., a radius no greater than 400 m) curve track. The friction-induced self-excited oscillation caused by the saturated wheel-rail creep force was used as the frequency-fixing mechanism of the wheel OOR wear, and the wheel polygonization induced via this oscillation was evaluated by finite element simulation. Furthermore, the influence of rail corrugation on the development of wheel OOR wear was analyzed, and it is found that, when the vehicle negotiates a small-radius curve track, an unstable oscillation of 87 Hz induced by the saturated creep force can lead to wheel 12th ∼ 13th-order OOR wear—mainly distributed along the inner wheel tread far from the wheel back. During vehicle operation, the vibrations caused by the wheel 12th ∼ 13th-order polygonization can excite the eigenmodes of the wheelset, leading to an increased wear intensity. In addition, wheel 12th-order polygonal wear interacts with the rail corrugation of the same wear wavelength but different phases, which can cause wheel 10th ∼ 11th- and 13th ∼ 17th-order polygonization.

Detailed Analysis of New York City Subway Pedestrian Incidents From 2019

This study analyzed New York Subway incident cases from 2019 to expand on the current understanding of subway train to human collisions. From the 263 incident cases available, 185 (70%) involved train to pedestrian contact. The fatality data were compared with published literature covering 1990 to 2007, showing reasonable agreement in age-, gender-, and borough distributions. The location of incidents was typically the station platform (84%). Four primary behaviors were exhibited by pedestrians before impact with the train. Jumping from the platform was the most common, followed by falling from the platform, walking along the tracks, and standing too close to the edge of the platform. A higher fatality rate was found for collisions that occurred at elevated stations (40%) compared with below-ground stations (27%). The two primary collision types were frontal- and side impact (on the train). The most common impact velocity was 40 to 48 km/h (25 to 30 mph). The most likely outcome of these interactions was a fatality (31%) with only 9% of subway–human interactions resulting in mild injuries. The data suggested that policies based on proactive countermeasures could reduce a significant portion of subway train–human collisions as the majority of preimpact activity occurred on the station platform. Further investigation into the difference in elevated and below-ground collisions may yield useful information, especially relating to the potential protection offered by the drainage trough. When simulating subway–human collisions for countermeasure design, equal consideration should be given to the three impact position types: standing, lying, and jumping.

Numerical Study of Train-induced Pressure on Platform Screen Doors of a Subway Station

We numerically investigate the train-induced transient pressure on the platform screen doors (PSDs) of an island-type platform in a subway station according to real scenarios and full-scale simulation to enhance understanding of the design and safe operation of subway trains. Two typical cases, namely, the non-stop and chasing cases, were examined, with the train’s speed variation well simulated throughout both cases. In the non-stop case, a train passes through the station without stopping; in the chasing case, a train stops at the station while another subsequent train approaches through the tunnel, which inevitably happens during rush hours. It is observed that the train generates a compression wave when it passes the tunnel’s ventilation shaft, similar to what occurs when entering a tunnel. In the non-stop case, the PSDs experience two positive and one negative pressure extremes in the whole process. The first positive peak results from an oncoming compression wave through the tunnel, while the second positive and negative peaks arise due to the passing of the train head and tail, respectively. In the chasing case, the stopped train at the platform leads to a blockage effect that significantly increases the pressure on the PSDs via the oncoming compression wave. This lateral pressure may result in the failure of proper operation of the PSDs, particularly during rush hours, with pressure lasting for roughly 5.7 seconds. It is also found that, compared to the fully sealed PSD, both the half-height and partial porous PSDs can significantly reduce the pressure load caused by the passing of the train head, with its maximum pressure load reduced by 38.7% and 38.2%, respectively. Therefore, if the pressure load on a fully sealed PSD is too high for structural design, one may consider the use of half-height and partial porous PSDs as an alternative. Our study offers crucial insights into the train-induced transient pressure on PSDs in a subway station island-type platform. It provides guidance on optimizing the pressure/operation problem on PSDs and offers valuable information for the safe design and operation of subway trains.

Pitting corrosion behavior of X70 steel in weakly alkaline solution under dynamic DC interference

Stray current discharged into the soil when subway trains operate will lead to fluctuation in the pipe-soil potential, which causes severe corrosion. In this work, the pitting corrosion behavior of X70 steel in a weakly alkaline simulated soil solution under different potential fluctuation ranges was studied. The influence of the fluctuation of the pipe-to-soil potential on the passivation film and pitting corrosion was studied using electrochemical measurement and surface characterization. X70 steel has passivation characteristics in the weakly alkaline solution. The passivation film is in a dynamic process of continuous growth or growth-dissolution due to the alternating polarization. The critical factor in inducing pitting corrosion is the failure to produce stable and dense passivation film or the instantaneous polarization potential exceeding the range of passivation potential. The passivation film's density determines the pitting's initiation and development trend. It is preliminarily found that the charge transfer resistance at the initiation stage of pitting has a good exponential function relationship with the pitting rate at the stable development stage, which is of great significance for the qualitative evaluation of the pitting rate.

An optimal selection method for exterior design schemes of subway trains based on multi-level gray relational analysis

To make appropriate decisions in the evaluation phase of the exterior design of subway trains, an optimal selection method was proposed based on multi-level gray relational analysis. The exterior design factors of subway trains were analyzed to construct an index system for design evaluation. The significance of each index was compared through an analytic hierarchy process. The correlation coefficient of each index in the plan was calculated through gray relational analysis to obtain the weighted correlation degree of each design scheme. The optimal selection of the exterior design of Guangzhou Metro Line 6 in China was considered as an example. Four types of subjects were recruited: professional designers, students majoring in design, subway train design experts, and subway passengers in Guangzhou. The weight of each index in the evaluation system was calculated using questionnaire scoring. Virtual simulation software was applied to evaluate the human factors related to each scheme. The indices in each plan were then scored to calculate the correlation coefficient and the overall correlation degree; and finally, the optimal selection was obtained. The results showed that it was practical to evaluate and optimize the exterior design of subway trains based on multi-level gray relational analysis. In the evaluation index system, the weights of technology, human factors, aesthetics, and culture were 0.517, 0.297, 0.099, and 0.087, respectively, which showed that technology had the greatest impact on the system, while human factors, aesthetics, and culture were useful complements. Our results showed that Design Scheme 1 was unsuitable as an optimization scheme due to the high escape window. Meanwhile, Design Scheme 2 was optimal overall, from a technical perspective. Design Scheme 3 was the best in terms of the escape window index (a human factor). Design Schemes 3 and 4 were optimally assessed from aesthetic and cultural perspectives. This study is conducive to the optimization of the exterior design of subway trains, can be used to inform design iteration, and provides a reference for the optimal selection of design schemes for other urban rail trains.

Assessment of metro-induced vibrations on photo-voltaic modules for their solar energy degradation potential

Structures in the vicinity of elevated, surface and subway metro trains are subjected to induced vibrations generated due to train movements. Nowadays PV (Photo-Voltaic) modules are heavily installed in the vicinity of metro rail. These metro vibrations are induced in PV modules mounted on adjacent structures, which accelerates the formation of cracks and micro-cracks in PV cells. PV modules show a detrimental effect on their performance and life due to these cracks. Therefore, to understand the vibration levels, this study aims to find out the frequency content and amplitude of vibrations at different locations in the metro vicinity. Vibrations are recorded at locations such as metro tracks, stations (elevated and ground), and adjacent buildings/structures where solar PV systems are installed. Vibrations induced in the nearby structures show peak velocity amplitudes in the frequency range of 20–250 Hz. In conclusion, the vibrations in the vicinity of the metro train are below the FTA limits. However, PV modules’ natural frequencies and induced vibrations fall in the same frequency range. This study shows that even when the induced vibrations are below the FTA limit, they can still cause a damaging effect on the PV modules, hence degrading solar energy generation.

Speed Limit of Linear Induction Motor Subway Trains Running through 65 m Radius Curves on Yard Line

Linear induction motor (LIM) subway yard line often have very-small-radius curves and small turnouts with “S”-shaped curves in the middle. The lateral stability of the train is low, and wheel-climb (slipway) derailments often occur at a speed of 10 km/h. To study the derailment safety and speed limit of a linear motor subway train running through yard line, a coupling dynamic model of the train-track system is established, fully considering the driving characteristics of the linear motor, characteristics of the linear motor train, and track structure. The safety of train derailment is judged by the over-limit time of the derailment coefficient. Under the premise of a safe operation, the variations in the derailment coefficient, out-of-limit time, wheel unloading rate, and wheel-axle lateral force with the train running speed are studied. When the train runs at speeds below 25 km/h, for both new and worn rails, the derailment coefficient and lateral force of the wheel axle at each speed exceed the safety limits, and are less affected by changes in the speed. The duration of the derailment coefficient is within the safety limit because the speed of crossing the curve is low, and thus the train will not overturn and derail. Rail wear reduces the train derailment safety through the yard line, while the wheel wear improves the train derailment safety through the yard line. Considering the actual state of the yard line (wheel-rail wear, irregularity, etc.), the speed of the linear motor subway train running through the yard line should be limited to below 15 km/h.

Применение генетических алгоритмов при решении задач планирования перевозочного процесса городской рельсовой транспортной системы

The article investigates the possibility to apply genetic algorithms at automation of planned schedules compilation for subway passenger train traffic. Research main goal – to improve automated system of planned schedule compilation for passenger trains for to provide for processes evenness at the use of various resources and consideration of existing limitations. Necessary definitions of resources and limitations on conditions of genetic algorithm usage are narrowed down to interconnected and unified tables. On probability approach basis, the influence of various combinations of genetic algorithm parameter values on population compositions in the process of search for effective results of transportation process planning for urban rail transport system has been studied. For investigation needs, computer software has been performed on high-level languages C# and Python. Genetic algorithm adaptation to the solution of the task for compilation automation of planned schedule of subway passenger train traffic has been made and there has been shown the algorithm applicability to automation of the complex of interconnected tasks for the transportation process planning: electric rolling stock turnout schedule compilation and locomotive team work schedule. There have been calculated probability values to get favorable outcome – the presence of all possible allele values at various combinations of the values of primary population size and allele needed quantity in the results of train traffic planned schedules.

Application research of piston wind and vertical axis wind turbine in the subway tunnel

When the above-ground space is insufficient to meet the traffic demand of people, the advantages of underground rail transit are particularly prominent. It has the advantages of short distance, unobstructed and so on, so it is imperative to develop underground rail transit. When the subway train is running, it will push the air forward. Due to the restriction of the tunnel’s inner wall on the air, a large number of piston winds are formed. Piston wind is harmful to train running and tunnel fire, but its air volume and wind speed are considerable. The vertical axis wind turbine has the advantages of small size and high power generation efficiency. It can be embedded in the inner wall of the subway tunnel, and it will not increase the resistance of the train. It can supply power for small electrical equipment in the subway tunnel.

Simulation method for train curve derailment collision and the effect of curve radius on collision response

A method of collaborative simulation of the train collision process using a rigid motion model and a flexible collision model is proposed to solve the problem of the low computational efficiency of the finite element numerical simulation of the train collision process. This study investigated the collision response of a train derailment hitting a platform with different curve radii based on an accident in which a subway train derailed and hit a platform. Based on the results, a collision damage index is proposed to assess the relative degree of damage of train derailment collisions at different curve radii. The results reveal that within a certain radius of the curve (when the impact distance D exists), there is a positive correlation between the curve radius and the collision damage index, and when the curve radius exceeds a certain value (when the impact distance D doesn’t exist), the train and platform don’t collide.