Urban Rail Transit Train Research Articles

Energy-Saving Optimization Method of Urban Rail Transit Based on Improved Differential Evolution Algorithm

The transformation of railway infrastructure and traction equipment is an ideal way to realize energy savings of urban rail transit trains. However, upgrading railway infrastructure and traction equipment is a high investment and difficult process. To produce energy-savings in the urban rail transit system without changing the existing infrastructure, we propose an energy-saving optimization method by optimizing the traction curve of the train. Firstly, after analyzing the relationship between the idle distance and running energy-savings, an optimization method of traction energy-savings based on the combination of the inertia motion and energy optimization is established by taking the maximum idle distance as the objective; and the maximum allowable running speed, passenger comfort, train timetable, maximum allowable acceleration and kinematics equation as constraints. Secondly, a solution method based on the combination of the adaptive dynamic multimodal differential evolution algorithm and the Q learning algorithm is applied to solve the optimization model of energy-savings. Finally, numeric experiments are conducted to verify the proposed method. Extensive experiments demonstrate the effectiveness of the proposed method. The results show that the method has significant energy-saving properties, saving energy by about 11.2%.

Dynamic Response and Riding Comfort Analysis of a Passenger-Train-Bridge System in Urban Rail Transit

To exactly study the riding comfort of passengers in urban rail transit trains, a coupling vibration model, including passengers, train, and bridge is proposed in this paper. According to the Lagrange Equation, the differential equations of motion of each part are derived, which are coupled with each other through displacement and dynamic interaction forces. A corresponding calculation program is compiled by the Fortran language. A representative steel-concrete composite girder bridge on Beijing Metro Line 5 is selected as the research background, the dynamic responses of passengers and train are simulated in detail, and the dynamic response differences between the passenger and carriage are compared. The passengers’ riding comfort is evaluated according to ISO-2631 Standard based on the simulated data. The result shows that passengers in the middle carriages of the train feel better than those in the head and tail ones. While in the same carriage, passengers on the middle seats feel better than those on both ends of it. If only vibration is considered, passengers will feel better in a fully loaded carriage than those with few passengers. The riding comfort of passengers will be gradually reduced with the increase of the train speed.

Modeling of cross line operation of urban rail transit trains based on passenger travel time

Cross line operation mode of urban rail transit can not only meet diversified travel needs of passengers and improve efficiency of passenger travel, but also shorten the time and space distance between suburban and urban core areas. In this paper, the travel time cost of different types of passengers is analyzed on the basis of considering the train selection probability for passengers to choose cross train or transfer. An optimization model of cross line operation organization is established with the objective function of minimizing the total travel time cost of passengers. The model is solved by genetic algorithm. The scheme of metro Line Ⅰ of city S crossing into Line Ⅱ is used as an example to verify the feasibility of the model, and the optimal train density under different train load rates is obtained. This study can provide a reference for the cross line operation organization of urban rail transit.

Study on Energy-Saving Optimization of Urban Rail Transit Train Timetable under Regenerative Braking

Energy-saving driving and regenerative braking energy utilization are two main ways to realize energy-saving optimization of urban rail transit train timetables. On the basis of the more mature energy-saving driving achievements of the predecessors, the absorption utilization rate of regenerative braking energy is improved by adjusting the dwell time of trains in the station so that while a train is braking, other trains in the same electric section are just under traction. In this paper, the overlap time between the traction and braking processes of different trains is used as a measure of the proportion of regenerative braking energy that is absorbed. In order to maximize this overlap time, an energy-saving optimization model of urban rail transit train timetable based on regenerative braking technology was established. To facilitate the solution, the nonlinear constraints are converted to linear at the time of model construction in this paper. In the solution, the spatio-temporal local rolling algorithm and the commercial optimization software ILOG CPLEX are used for the solution. The solution results show that the method in this paper can effectively improve the absorption and utilization of regenerative braking energy.

Research on Energy Saving Optimization Technology of Urban Rail Transit Train Operation

Research on Energy Saving Optimization Technology of Urban Rail Transit Train Operation

Real-time energy saving optimization method for urban rail transit train timetable under delay condition

The global energy crunch and rising demand for electricity make it all the more important to develop energy-efficient timetable for urban rail transit trains. Under normal circumstances, the train can operate normally according to the energy-saving timetable that has been formulated. However, trains may deviate from the original schedule and increase energy consumption due to station delays. For this, how to quickly restore the train to an efficient state and effectively transport the delayed passengers to the destination as soon as possible is a challenging problem. Therefore, this paper proposed a two-stage optimization method to solve the above problem. In the first stage, an improved differential evolution algorithm was used to optimize the energy-saving operation strategy of the train without delay, and the optimal running time-energy consumption solution set of the train in the redundant running time of each section on the entire line was obtained. Then, based on this, the second stage proposed a rapid iterative method to optimize and reschedule the timetable of the delayed train in the remaining sections, and an efficient solution was obtained. Finally, Nanning Rail Transit (NNRT) Line 5 is selected for a case study, and the proposed model and method are verified. Compared with the existing solution that temporarily shortens the running time of the next section in the delayed station, the proposed method reduces the energy consumption by 3.32% on average, and the average calculation time is about 0.36 s, which showed that the method is effective and meets the real-time requirements.

A Two-Stage Train Delay Prediction Method Based on Data Smoothing and Multimodel Fusion Using Asymmetry Features in Urban Rail Systems

During the operation of urban rail transit trains, train delays have a great negative impact on subway safety and operation management. It is caused by various external environmental disturbances or internal equipment failures. In order to better grasp the situation of train delays, adjust train operation schedules in time, and improve the quality of rail transit command and transportation services, this paper proposes a two-stage train delay prediction method based on data smoothing and multimodel fusion. In the first stage, the Singular Spectrum Analysis (SSA) method is used to smooth the train operation data, and the smoothed components and residual components are extracted. In the second stage, we use different machine learning methods to train the smoothed data and use the K -nearest neighbor (KNN) method to fuse different trainers. Finally, the predicted values of the smoothed and residual components are combined to improve the overall performance of the train delay prediction model, especially under asymmetry features. The research results show that the prediction accuracy of the two-stage train delay prediction method based on KNN multimodel fusion is significantly better than that of the independent machine learning model.

Rescheduling Urban Rail Transit Trains to Serve Passengers from Uncertain Delayed High-Speed Railway Trains

This paper develops a multi-objective mixed-integer linear programming model for the problem of robust rescheduling for capacitated urban rail transit (URT) trains to serve passengers from delayed high-speed railway (HSR) trains. The capacity of each extra train is not assumed to be unlimited in this paper. Robust passenger assignment constraints are developed to ensure that delayed passengers can board the URT trains under different random delay scenarios of HSR operations. Robust dispatching constraints of URT trains are designed for a stable disrupting number of URT trains across different scenarios. The multi-objective model is used to maximize the number of expected transported passengers and minimize the number of extra trains and operation-ending time of all extra trains. An iterative solution approach based on a revised version of the epsilon-constraint method combined with the weighted-sum method is designed for the computation of the multi-objective model. Computational experiments are performed on the Beijing URT lines and the Beijing-Shanghai HSR line. We evaluate the impact of the robustness constraints of passenger assignment and the number of extra trains to ensure that the number of trains are maintained and the passengers can successfully take the trains during different delayed scenarios.

A hierarchical coordinated control strategy based on multi-port energy router of urban rail transit

The multi-port energy router (ER) is an effective topology for integrating train traction load, AC load, the energy storage system and photovoltaic(PV) energy. The start and stop process of urban rail transit trains and the access of distributed energy sources to rail transit ER lead to serious fluctuations of DC bus power, so it is necessary to route energy between different ports, involving multi-operating modes, while seamless switching is a major challenge. In this paper, a hierarchical coordinated control strategy is proposed to enable the multi-port ER to operate in a coordinated fashion under the conditions of train parking, acceleration, constant power driving and deceleration, and to switch seamlessly under various working conditions. The energy central dispatching layer sends working condition instructions by sampling the state information of each port, while the microgrid control layer adopts centralized control, receiving upper working condition instructions and sending drive signals to the local control layers to maintain the balanced energy flow of each port. In the local control layers, the PV adopts the improved perturbation and observation method of power control (PC-P&O), while the ES system adopts voltage loop control with an SOC influence factor, voltage loop control with switching factor and power loop control according to the different working conditions, so as to transmit the required train load power accurately and maintain the stability of the DC bus voltage. Finally, the effectiveness of the proposed hierarchical coordination control is verified by MATLAB/Simulink simulations.

Joint optimization of train scheduling and dynamic passenger flow control strategy with headway-dependent demand

Focusing on massive demand and high-frequency trains in urban rail transit, this paper proposes a novel joint optimization approach for train scheduling and dynamic passenger flow control strategy under oversaturated conditions to minimize the total number of waiting passengers. In view of the relationship between the number of boarding/alighting passengers and the dwell time of trains, the problem is formulated as a mixed-integer linear programming (MILP) model. This model can achieve the trade-off between the utilization of trains and passengers. The ILOG CPLEX is adopted to solve the proposed model. And a real-world case study of the Beijing Metro Line 5 is given to demonstrate the feasibility and effectiveness. Through jointly optimizing train schedule and flow control, the average boarding rate of passengers increases from 36.34% to 87.55%. The results show that the proposed flow control is effective in alleviating the oversaturated situations at platforms and trains.

Real-Time Energy Saving Optimization Method for Urban Rail Transit Train Timetable Under Delay Condition

Real-Time Energy Saving Optimization Method for Urban Rail Transit Train Timetable Under Delay Condition

Real-Time Energy Saving Optimization Method for Urban Rail Transit Train Timetable Under Delay Condition

Real-Time Energy Saving Optimization Method for Urban Rail Transit Train Timetable Under Delay Condition

A Two-Layer Surrogate-Assisted Fish Migration Optimization for Urban Rail Transit Train Route Optimization

A Two-Layer Surrogate-Assisted Fish Migration Optimization for Urban Rail Transit Train Route Optimization

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.

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.

Research on Non-catenary Power Supply Technology

The traction power supply mode of urban rail transit trains is mainly divided into two categories: contact power supply and contactless power supply. Among them, contactless power supply mode has advantages of cost saving, unrestricted operation area, energy conservation and environmental protection. Therefore, some domestic and foreign institutions have begun to carry out research in related fields and practical application. Based on the “Battery and super capacitor” train hybrid energy storage system, we study the contactless power supply technology in this paper, the description and conclusion can provide a reference for the further research of contactless power supply technology together.

Failure analysis on rubber universal spherical joints for rail vehicles

Considering the large quantity of passengers in a running rail vehicle, its safety must be paid special attention to, which relies on the reliability of every critical component. Spherical universal joint is widely used in the suspension device of the gearbox in the transmission of railway vehicles for its functions of damping and cushioning. Since it’s commonly made of rubbers rather than the familiar metallic materials, its degradation behaviors and failure mechanisms have not been systematically investigated. In this study, multiple rubber spherical universal joints used in the urban rail transit train were found cracked and sticky during maintenance. Its design lifetime was 5 years, but this kind of failure occurred in <2 years, which posed a threat to the safe operation of the train. In order to identify the root causes of the failure, the physical, chemical, mechanical properties and the surface morphologies of the failed joints were characterized by a series of methods. The results showed that the corrosive solvents introduced during installation was the root cause of the failure, which was further aggravated by the oversizing and segregation of the filler particles in the rubber and the high crosslinking density of the rubber. Based on these failure causes, countermeasures were proposed to prevent the occurrence of similar failure again.

Exploration of Automatic Car Washing Scheme for Urban Rail Transit Trains

Exploration of Automatic Car Washing Scheme for Urban Rail Transit Trains

Research on speed sensor fusion of urban rail transit train speed ranging based on deep learning

Abstract The speed sensor fusion of urban rail transit train speed ranging based on deep learning builds a user-friendly structure but it in-turn increases the risk of traffic that significantly challenges its safety and transportation efficacy. In order to improve the operation safety and transportation efficiency of urban rail transit trains, a train speed ranging system based on embedded multi-sensor information is proposed in this article. The status information of the train is acquired by the axle speed sensor and the Doppler radar speed sensor; however, the query transponder collects the status information of the train, and is used in the embedded system. Various other modules like adaptive correction, idling/sliding detection and compensation of speed transition/sliding are used in the proposed methodology to reduce the vehicle speed positioning errors due to factors such as wheel wear, idling, sliding, and environment. The results show that the running time of the train is 1000s, the output period of the axle speed sensor is 0.005s and the accelerometer output period is 0.01s. The output cycle of doppler radar is observed to be 0.1s, the output cycle of the transponder is 1s and the fusion period of the main filter is observed as 1s. The train speed ranging system of the embedded multi-sensor information fusion system proposed in this article can effectively improve the accuracy of the train speed positioning.

Research on Synchronverter-Based Regenerative Braking Energy Feedback System of Urban Rail Transit

Generally running with frequent braking over short distances, the urban rail transit train generates great quantities of regenerative braking energy (RBE). The RBE feedback system can effectively recycle RBE and give it back to the AC grid. However, the lack of damp and inertia of generators makes conventional PWM RBE feedback system more sensitive to power fluctuations. To address this issue, a synchronverter-based RBE feedback system of urban rail transit is designed in this paper. First, the structure of the feedback system is presented. Then, the synchronverter-based control strategy with greater flexibility and higher stability is fully discussed. Furthermore, the parameter design of the system is analyzed in detail. Finally, simulation results and experimental results are provided to show the good dynamic performance of the system. Using this synchronverter-based approach, the system supplies traction power to the traction network when the train accelerates and gives the RBE back to the AC grid when the train brakes, in light of the variation of the DC bus voltage. Moreover, the system can be self-synchronized with the AC grid and make corresponding power management on the basis of changes in the voltage amplitude as well as the frequency of the grid. In this sense, the RBE feedback system becomes more flexible, effective and robust.