Urban Rail Train Research Articles

EMD and GNN-AdaBoost fault diagnosis for urban rail train rolling bearings

Rolling bearings are the most prone components to failure in urban rail trains, presenting potential danger to cities and their residents. This paper puts forward a rolling bearing fault diagnosis method by integrating empirical mode decomposition (EMD) and genetic neural network adaptive boosting (GNN-AdaBoost). EMD is an excellent tool for feature extraction and during which some intrinsic mode functions (IMFs) are obtained. GNN-AdaBoost fault identification algorithm, which uses genetic neural network (GNN) as sub-classifier of the boosting algorithm, is proposed in order to address the shortcomings in classification when only using a GNN. To demonstrate the excellent performance of the approach, experiments are performed to simulate different operating conditions of the rolling bearing, including high speed, low speed, heavy load and light load. For de-nosing signal, by EMD decomposition is applied to obtain IMFs, which is used for extracting the IMF energy feature parameters. The combination of IMF energy feature parameters and some time-domain feature parameters are selected as the input vectors of the classifiers. Finally, GNN-AdaBoost and GNN are applied to experimental examples and the identification results are compared. The results show that GNN-AdaBoost offers significant improvement in rolling bearing fault diagnosis for urban rail trains when compared to GNN alone.

An integrated approach for the energy-efficient driving strategy optimization of multiple trains by considering regenerative braking

Abstract With the rapid development of urban rail transit networks, the energy consumption problem of urban rail trains becomes more and more prominent. A critical issue is to reduce the energy consumption of trains through advanced control and optimization techniques. The majority of existing studies in this field focus on (1) the optimization of single train operation strategy and (2) the scheduling of multiple trains, separately. In this paper, we propose an integrated energy-efficient operation optimization method for multiple trains in multiple interstations by considering regenerative braking. In particular, this paper integrates the energy-efficient operation strategy with optimized train timetable under the operation scenario of two trains in multiple interstations. First, a genetic algorithm is used to optimize the energy-efficient operation strategy for single train in multiple interstations and obtain the relationship between the operation time and operation energy consumption of trains. Then, a particle swarm optimization method is adopted to obtain the optimal operation time of trains (i.e. train timetable) for the purpose of minimizing the overall energy consumption. Finally, real-world case studies based on the operation data of the Beijing subway line 7 are presented to verify the effectiveness of the proposed approach. Numerical experiments show that the proposed approach by optimizing the train operation strategy and timetable can reduce the total energy consumption by 16.24% compared with the real-world train operation strategy.

Research on Multi-Objective Real-Time Optimization of Automatic Train Operation (ATO) in Urban Rail Transit

The determination and optimization of Automatic Train Operation (ATO) control strategy is one of the most critical technologies for urban rail train operation. The practical ATO optimal control strategy must consider many goals of the train operation, such as safety, accuracy, comfort, energy saving and so on. This paper designs a set of efficient and universal multi-objective control strategy. Firstly, based on the analysis of urban rail transit and its operating environment, the multi-objective optimization model considering all the indexes of train operation is established by using multi-objective optimization theory. Secondly, Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to solve the model, and the optimal speed curve of train running is generated. Finally, the intelligent controller is designed by the combination of fuzzy controller algorithm and the predictive control algorithm, which can control and optimize the train operation in real time. Then the robustness of the control system can ensure and the requirements for multi-objective in train operation can be satisfied.

基于T-S模糊模型的预测控制算法在城轨列车制动控制中的应用

基于T-S模糊模型的预测控制算法在城轨列车制动控制中的应用

Supercapacitor State Based Control and Optimization for Multiple Energy Storage Devices Considering Current Balance in Urban Rail Transit

The use of supercapacitors (SCs) to store regenerative braking energy from urban rail trains is able to achieve a good energy saving effect. This paper analyzes the current balance method of stationary energy storage devices (ESDs). At the beginning of the paper, the mathematical model of the DC traction power system, which includes trains, ESDs and traction substations, is established. Next, based on this, the SC state-based control strategy (SCSCS) is proposed, which can adjust the charging voltage of the ESD according to the SC voltage and current, then the charging current of the ESD can be reasonably distributed under the voltage difference of ESDs, and the SC voltage and current stress can be reduced. In order to determine the optimal controlling parameters, the optimization model is proposed and solved by the genetic algorithm. The analysis of the case study also shows the effectiveness of the proposed control strategy and optimization algorithm. Finally, the rationality of the proposed strategy is verified by experiments.

An adaptive stable observer for on board auxiliary inverters with online current identification strategy

An adaptive stable observer with output current online identification strategy for the auxiliary inverters applied in advanced electric trains, such as high speed railway, urban rail, subway and maglev trains, is proposed. The designed observer is used to estimate the state variables, i.e. controllable duty ratio and current components in d-q-o rotary reference frame. The convergence of the observer estimation error is analyzed with consideration of uncertain level variation of input voltage at direct current (DC) side and sufficient conditions are given to prove its practical stability. Experimental results are shown to confirm the effectiveness of the proposed observer.

Pareto optimal train scheduling for urban rail transit using generalized particle swarm optimization

In urban rail transport, train timetable plays a crucial role, whose quality determines the whole system’s performance to a large extent. In practical urban rail operation, two contradictive aspects—service quality and operation cost—should be considered during train scheduling. A good train timetable should achieve considerable service quality with as little operation cost as possible. Previously, many studies have been conducted specific to urban rail train scheduling, although most of them do not put enough emphasis on its multi-objective nature. In this article, therefore, Pareto optimal urban rail train scheduling which can give more instruction to practical operation is studied. First, referring to some existing studies, the problem is reasonably defined, which takes time-dependent origin–destination demand as the input and aims at minimizing the passengers’ total travel time and the number of used train stocks. Then, an efficient iteration algorithm and a valid train stock assignment procedure are designed to calculate the passengers’ total travel time and required train stock number, respectively. On that basis, the studied problem is reasonably formulated as a bi-objective optimization model and a Pareto-based particle swarm optimization procedure is designed to solve it. Finally, with two different scaled urban rail lines, the whole methodology is illustrated and the algorithm is tested.

An Improved Central 60° Synchronous Modulation for High Transient Performance with PMSM Stator Flux Control Used in Urban Rail Transit Systems

Central 60° synchronous modulation is an easy pulse-width modulation (PWM) method to implement for the traction inverters of urban rail trains at a very low switching frequency. Unfortunately, its switching patterns are determined by a Fourier analysis of assumed steady-state voltages. As a result, its transient responses are not very good with over-currents and high instantaneous torque pulses. In the proposed solution, the switching patterns of the conventional central 60° modulation are modified according to the dynamic error between the target and actual stator flux. Then, the specific trajectory of the stator flux and current vector can be guaranteed, which leads to better system transients. In addition, stator flux control is introduced to get smooth mode switching between the central 60° modulation and the other PWMs in this paper. A detailed flow chart of the control signal transmission is given. The target flux is obtained by an integral of the target voltage. The actual PMSM flux is estimated by a minimum order flux state observer based on the extended flux model. Based on a two-level inverter model, improved rules in the α-β stationary coordinate system and equations of the switching patterns amendment are proposed. The proposed method is verified by simulation and experimental results.

Distributed Auxiliary Inverter of Urban Rail Train—Load Sharing Control Strategy Under Complicated Operation Condition

Paralleling is the development tendency of the auxiliary inverter. This paper analyzes the problems of the parallel process in detail. First, for inherent contraction between voltage regulation performance and current sharing performance, the paper adopts the resistive droop method. Second, the paper improves dynamic performance and reliability of the droop method by improving power calculation and introducing the whole cycle adaptive droop method. Third, in order to solve the unshared current problem caused by inconsistent parameters, the paper increases active power proportion droop coefficient, and introduces voltage compensation strategy to compensate voltage drop caused by increased proportion droop coefficient. Fourth, the auxiliary parallel system has complicated load characteristics; the paper proposes voltage compensation strategy to compensate voltage drop caused by the pump load. This paper utilizes three-phase total reactive power to droop frequency and active power of each phase to droop amplitude, unbalanced current can be shared. This paper introduces special virtual impedance technology to solve the harmonic current sharing problem caused by the nonlinear load. Finally, the effectiveness of above theory is fully verified by simulation and experiment.

Distributed Auxiliary Inverter of Urban Rail Train—The Voltage and Current Control Strategy Under Complicated Load Condition

With increasingly prominent role of rail transit in the entire urban transport system, an auxiliary inverter is used increasingly. The complicated and fluctuating load condition of the auxiliary inverter implies special designs about structure and control strategy are necessary. For this purpose, a comprehensive control strategy is proposed. First of all, this paper proposes a structure that is capable of suppressing unbalanced voltage. Second, the control strategy based on the resonant controller is proposed, which can balance split capacitors voltage, is capable of suppressing the effect of unbalanced load and nonlinear load. This paper introduces the design method of the control system in detail. Then, this paper simulates the proposed comprehensive control strategy in MATLAB. Finally, experimental results are presented, which fully demonstrate the excellent performance of the comprehensive control strategy.

Safety Assessment for Electrical Motor Drive System Based on SOM Neural Network

With the development of the urban rail train, safety and reliability have become more and more important. In this paper, the fault degree and health degree of the system are put forward based on the analysis of electric motor drive system’s control principle. With the self-organizing neural network’s advantage of competitive learning and unsupervised clustering, the system’s health clustering and safety identification are worked out. With the switch devices’ faults data obtained from the dSPACE simulation platform, the health assessment algorithm is verified. And the results show that the algorithm can achieve the system’s fault diagnosis and health assessment, which has a point in the health assessment and maintenance for the train.

A Survey on Energy-Efficient Train Operation for Urban Rail Transit

Due to rising energy prices and environmental concerns, the energy efficiency of urban rail transit has attracted much attention from both researchers and practitioners in recent years. Timetable optimization and energy-efficient driving, as two mainly used train operation methods in relation to the tractive energy saving, make major contributions in reducing the energy consumption that has been studied for a long time. Generally speaking, timetable optimization synchronizes the accelerating and braking actions of trains to maximize the utilization of regenerative energy, and energy-efficient driving optimizes the speed profile at each section to minimize the tractive energy consumption. In this paper, we present a fully comprehensive survey on energy-efficient train operation for urban rail transit. First, a general energy consumption distribution of urban rail trains is described. Second, the current literature on timetable optimization and energy-efficient driving is reviewed. Finally, according to the review work, it is concluded that the integrated optimization method jointly optimizing the timetable and speed profile has become a new tendency and ought to be paid more attention in future research.

Hybrid stop schedule of urban rail train

Purpose: In order to better serve the transport demand of urban area by rail, target at the Ur-ban Rail Train Stop Schedule problem. Design/methodology/approach: Bi-level mathematical programming model and game relation was used. Findings: A 0-1 bi-level mathematical programming model for urban rail transit hybrid Stop Schedule is developed when game relation between train Stop Schedule and passenger transfer choice is considered. Research limitations/implications: The research is still in progress. Practical implications: ChongQing urban rail line 2 was taken as an example, the practical application of the model has proved its feasibility and efficiency. Originality/value: A 0-1 bi-level mathematical programming model for urban rail transit hybrid Stop Schedule is developed. The upper level model is Stop Schedule targeting at the optimal profit from the operators side. The lower level model is passenger routing aims to minimize total travel time. According to its features, the bi-level model is integrated in order to be directly solvable by optimizing software.

The New Structure Design and Analysis of Energy Storage of Flywheel of Split Rotor

The braking of the rail transit train consumes a great quantity of energy, and the thermal energy produced in the process of braking can affect the normal operation of the transit train. Thus recycling the braking energy becomes a research hotspot of urban rail train. This paper made an overall analysis of regenerative braking process, the rationale, and the main features and then put forward the optimizing the structure of the composite flywheel concept and design calculation method. This paper also designs a new flywheel structure which can be applied on urban rail operating system. The new flywheel structure should be checked by finite element method and the radius of the rotor should be defined under the condition of meeting the requirements of carbon fiber material strength. Meanwhile, compared with the solid flywheel under the same condition, analysis shows that the maximum rotary inertia of the new flywheel and the quality energy density increased, and the discharge depth also perks up.

Research on Urban Rail Train Passenger Door System Fault Diagnosis Using PCA and Rough Set

Train passenger door is the key system for operation and maintenance of urban rail train. In this paper, working process of the passenger door system of urban rail train is analyzed and the mathematical model is established. Firstly, the method of parameter estimation is used to obtain physical parameters of doors in different working conditions. Then fault diagnosis experiment is carried out on train passenger door with principal component analysis and rough set theory. In the end, fault diagnosed accuracies under different time settings of opening and closing profiles with the test rig are verified.

Airborne sound insulation of aluminum extrusion structural walls of an urban rail train

Airborne sound insulation of aluminum extrusion structural walls of an urban rail train

Design of Integrated Monitoring and Early Warning System of Urban Rail Transit Train Running State

The monitoring and warning of urban rail transit is the core of operation management, and the breadth and depth of the monitoring range directly affect the quality of urban rail transit operation. For the current domestic monitoring system, most of the critical equipments and technologies are introduced from abroad; it is diseconomy, and also causes hidden danger. Realizing the localization of monitoring and early warning system is imperative. Based on the analysis of the present situation of urban rail transit operation safety at home and abroad, the paper proposes to use integrated technology to design basic framework of monitoring and warning system of urban rail train, and puts forward the critical technologies to realize the system. Compared with the existing monitoring system, the integrated monitoring system has the characteristics of wide monitoring range, clear division of labor, centralized management, coordination and integration operation and intelligent management, and embodies the concept of people-oriented. It has scientific significance for future construction of domestic Integrated Monitoring and Early Warning System (IMEWS) of urban rail transit.

Re-attack on a three-party password-based authenticated key exchange protocol

A password based authenticated key exchange protocol is of practical usefulness in the protection of sharing of urban rail train sensor monitoring data. However, many password-based protocols in the literature were not secure. Recently, Huang presented a simple and efficient three-party password-based authenticated key exchange protocol. However, Yoon et al. found it had some security weaknesses. In this paper, we further show it has another critical security weakness, which opens door to a partition attack (offline dictionary attack). Thereafter we propose an enhanced protocol that can defeat the attacks described (including Yoon et al.’s attacks) and yet is reasonably efficient. Furthermore, our protocol can resist against the stolen-verifier attacks and achieve the provable security.

Braking Performances of Urban Rail Trains

In the line design and operation management of urban rail transit, braking performance of trains is a complicated but important part. This study analyzes the braking performances of urban rail trains by case analysis of gradients of rail lines, weights of trains, utilization ratios of braking force, speeds of trains at their initial brakes. Countermeasures to improve the braking effect are proposed accordingly. Through computation and result analysis, the influences form the factors are identified, namely, gradients of rail lines, weights of trains, utilization ratios of braking force, speeds of trains at their initial brakes. The study results are able to improve the work of designing urban rail lines, choices of technical parameters of trains, layouts of signals and speed limits of rail lines.