Urban Rail Vehicle Research Articles

A Condition Evaluation Simplified Method for Traction Converter Power Module Based on Operating Interval Segmentation

In the actual operation of urban rail vehicles, it is essential to evaluate the condition of the traction converter IGBT modules. Considering the fixed line and the similarity of operation conditions between adjacent stations, this paper proposes an efficient and accurate simplified simulation method to evaluate IGBT conditions based on operating interval segmentation (OIS). Firstly, this paper proposes the framework for a condition evaluation method by segmenting operating intervals based on the similarity of average power loss between neighboring stations. The framework makes it possible to reduce the number of simulations to shorten the simulation time while ensuring the state trend estimation accuracy. Secondly, this paper proposes a basic interval segmentation model that uses the operating conditions as inputs to implement the segmentation of the line and is able to simplify the operation conditions of entire line. Finally, the simulation and analysis of the temperature and stress fields of IGBT modules based on segmented intervals completes the IGBT module condition evaluation and realizes the combination of lifetime calculation with actual operating conditions and internal stresses. The validity of the method is verified by comparing the interval segmentation simulation with actual test results. The results show that the method can effectively characterize the temperature and stress trends of traction converter IGBT modules in the whole line, which could support the fatigue mechanism and lifetime assessment reliability study of IGBT modules.

Failure analysis of inner wall of X-10 brake discs for urban rail vehicles

Some X-10 type brake discs for urban rail vehicles were examined by fluorescent magnetic particle inspection test, and the magnetic trace accumulation was observed at the root of the connecting claw of the brake discs. In this work, the causes of failure for the brake discs are analyzed and discussed. The chemical composition, metallographic structure, and mechanical property of the failure samples were characterized by means of X-ray energy dispersive spectrometry, metallographic microscope, scanning electron microscopy, and an electronic universal material-testing machine. At the same time, the stress and crack propagation states were analyzed by numerical simulation, braking dynamic and fatigue tests, respectively. Based on the fracture mechanics theory, the residual fatigue life was also predicted. The failure reason of the inner wall of brake disc was that the fatigue crack occurred at the root of the connecting claw of the brake disc body, and the crack source was taken from graphite sheets exposed on the surface of the grey cast iron matrix. The results of the numerical simulation showed that the larger thermal stress acted on the graphite sheets at the root of the connecting claw, and promoted the crack to expand along the path of the graphite sheets. The results of the braking force and fatigue tests showed that there was stability propagation of the crack. Finally, some suggestions and prevention for brake discs are provided.

Discussion on the regional cultural semantic design of urban rail vehicles

Discussion on the regional cultural semantic design of urban rail vehicles

Research on Direct Drive Technology of the Permanent Magnet Synchronous Motor for Urban Rail Vehicles

Compared with the traditional gear reduction mechanism of the asynchronous motor, the permanent magnet synchronous motor (PMSM) direct drive technology has obvious advantages and has attracted increasing attention. We analyzed the advantages of the PMSM direct drive technology and put forward the hollow shaft structure of the coupling to reduce the impact force of the wheel and rail, additional noise, vibration, and loss. We deeply studied the topology and mathematical model of the PMSM. To keep the maximum running speed unchanged, it is necessary to conduct a flux weakening control above the rated speed to increase the speed regulation range of the PMSM. To prevent frequent switching jitter at the transition point and smooth the transition between different weak magnetic fields, we designed a new flux-weakening controller to control the current. Simulation results have been presented to verify the proposed approach efficiency. Taking the PMSM system train on Suzhou Metro line 3 as an example, the on-site energy consumption test was carried out. The energy consumption of the PMSM direct drive and asynchronous motor gear mechanism was compared. The energy consumption of the PMSM direct drive is increased by 16.50%. The flexible plate coupling can alleviate the adverse effects of vibration and improve the reliability of train operation. Finally, we put forward the technical difficulties and challenges of the PMSM direct drive technology. We need to optimize the mass distribution of the direct drive bogie to improve the dynamic performance of the bogie, the heat dissipation conditions, and the accurate control of the PMSM. It will have reference value for the development of the PMSM direct drive in the future.

Intelligent Diagnosis of Bogie Traction Seat Based on PCA-OVO and SVM Optimized by Modified Arithmetic Optimization Algorithm

The bogie traction seat is the main part of urban rail vehicles and its fault status will affect the safe and smooth operation of the vehicles. For the low accuracy of the traditional detection methods, an intelligent fault diagnosis model of the traction seat based on principal component analysis with one versus one (PCA-OVO) and support vector machine (SVM) optimized by modified arithmetic optimization algorithm is proposed. Firstly, for the difficulty of high-frequency data collection under real working conditions, the simulation platform of the bogie of an urban rail vehicle is built, and the vibration signals of the traction seat are collected and processed in different domains, and then the feature extraction and fusion method based on PCA-OVO is used to obtain the sensitive feature set of the traction seat. Finally, the SVM intelligence recognition model is constructed based on the sensitive feature set data, and its parameters are optimally combined and selected by the modified arithmetic optimization algorithm after introducing the cosine factor. The experiments prove the effectiveness of the model. Experimental results show that the model is effective and provides a new model for fault diagnosis of traction seat of urban rail vehicles.

Cooperative braking of urban rail vehicles with Koopman model predictive control

AbstractBraking control of urban rail vehicles with multiple carriages is critical to ensure the safe operation of urban rails. However, existing decentralized braking control methods lead to the inconsistent speed and excessive coupler force among carriages, which compromises the operation safety of urban rails. To address this issue, a cooperative braking strategy is proposed for urban rail vehicles based on Koopman model predictive control method. First, a cyber‐physical model is established, where the physical layer characterizes the dynamic model of multiple carriages using the Koopman operator. The cyber layer represents the communication topology of carriages with graph theory. Second, a cooperative braking controller is designed with the distributed model predictive control method. An optimisation problem is formulated to minimize the speed inconsistency and relative displacement difference among carriages. Third, extensive simulations under various scenarios, including normal and extreme operating conditions, are conducted to verify the effectiveness of the proposed method. Simulation results show that, compared with the classical decentralized method, the proposed braking method reduces the average relative displacement by 78% while reducing the speed error by 29%.

Achieving high-resolution 3D acoustic imaging in a large-aspect-ratio cabin by the non-synchronous measurements

The resolution of conventional acoustic imaging methods in a large-aspect-ratio cabin is reduced seriously by array parameters limitation and reverberation. The non-synchronous measurements technique breaks through the limitation of array shape and the number of microphones. This method can approximate the result of synthetic large-aperture array acoustic imaging. The increase in the number of microphones and low-rank constraint assumption in non-synchronous measurements suppress the reverberation interference. The low-rank constraint filters out the eigenvalues of the reverberation sound other than the main noise sources, which is acted as an eigenvalue filter. It has been demonstrated that non-synchronous measurements with 3D beamforming can improve the resolution of acoustic imaging in cubic space, but the related research on the large-aspect-ratio cabin is still missing. The non-synchronous measurements method is applied to achieve high-resolution acoustic imaging in a large-aspect-ratio cabin in this paper. The array measurement scheme is investigated comprehensively, including the number of non-synchronous measurements, the array step distance and appropriate spatial basis functions. The experimental results show that the non-synchronous measurements can achieve high-resolution 3D acoustic imaging in the cabin of an urban rail vehicle.

Health Status Assessment for New Urban Rail Vehicle Traction Systems Based on Cross Entropy and SVM

A health status assessment method based on cross entropy and support vector machine (SVM) is proposed for the new urban rail vehicle traction systems. First, an index system for health assessment of the traction system is established, and combined weights of the index layer are obtained via cross entropy. Then, an SVM assessment model considering actual operating data and each status level of the traction system is established. Finally, the model is simulated in Matlab to obtain assessment results. The results indicate that the proposed method can provide the health status information of the traction system intuitively and complete the health status assessment of the traction system of the new urban rail vehicle effectively, by exploiting the traction system's layered analysis model. The health status can be assessed accurately and reliably by adopting the cross entropy theory and SVM theory.

Development of the urban rail vehicle acoustic model

Noise emitted by urban rail transport is one of the four main sources of noise in urban agglomerations (according to the Environmental Noise Directive 2002/49/EC), and therefore it is subject to cyclical quantification and control. For this purpose, various types of acoustic maps are made, however, as scientific research shows, not every acoustic model is best suited for conducting effective quantitative analyses. Another problem is to carry out effective qualitative analyses, which additionally represent structural distribution of rolling noise generated by rail vehicles. The authors of the article present an original model of acoustic signature emitted by a selected type of urban rail vehicle in normal operation. To carry out the investigation, several dozen sound measurements were made according to own research methodology as well as several acoustic roughness measurements of wheel and rail rolling surfaces. The most important conclusion of this paper is the fact that based on validation and verification it can be concluded that the developed model is very well suited to estimate octave spectra of sound levels in relation to distance from the source (range 1–10 m) and speed (range 40–70 km/h) of a passing city rail vehicle.

Intelligent Diagnosis Model of Traction Seat of Urban Rail Vehicle Based on Harris Hawks Optimization

Traction seat is an important connecting part of urban rail vehicle, which plays an important role in maintaining smooth running and power transmission of the vehicle body. Timely diagnosis of early failure of traction seat is the key to ensure the safe operation of urban rail vehicles. In order to realize the intelligent diagnosis of traction seat, a multialgorithm fusion scheme based on the Harris Hawk algorithm (HHO) is proposed to realize the fault diagnosis of traction seat. Firstly, the early mechanism of traction seat was studied, and the simulation experiment platform of urban rail vehicle traction seat was built to obtain the vibration data of the early crack traction seat model, so as to facilitate the simulation experiment research. Then, the vibration data of the traction seat were processed by HHO optimized variational mode decomposition (HVMD) to obtain several intrinsic mode functions (IMFs). Secondly, the multiscale permutation entropy (MPE) of each IMF is quantified and its average value is used to construct the energy characteristic vector. Finally, feature vectors are input into the HHO optimized support vector machine (HSVM) model to train a pattern recognizer. Through Python simulation verification, the results show that the model can accurately extract the characteristic information of traction seat and accurately identify the fault type, and the recognition rate reaches 100%.

An Improved Force Characteristic Curve Fitting Algorithm of Urban Rail Vehicles

In this paper, an improved force characteristic curve fitting memetic algorithm of urban rail vehicles is proposed for establishing precise train operation models. In order to improve the memetic algorithm global convergence, three strategies are adopted. In the improved memetic algorithm framework, an improved moth-flame optimization is used in global search; an improved simulated annealing is applied in local search; a new learning mechanism incorporated into reverse learning is adopted. Experimental simulation results under real-time data monitoring system show that the improved memetic algorithm proposed in this paper can increase the optimization performance effectively so more perfect force characteristic curve fitting effort can be obtained, and the calculated average force error and max running distance error can be reduced effectively. Moreover, the above relative results indicate that the train energy consumption model using the improved force characteristic curve fitting algorithm can obtain more precise energy consumption. Obviously, the improved force characteristic curve fitting algorithm can effectively improve the curve fitting precision.

Analysis of Anti-skid Protection Measures for Braking System of Urban Rail Vehicles

Analysis of Anti-skid Protection Measures for Braking System of Urban Rail Vehicles

Design of a Metro Train and Structural Analysis of the Metro Vehicle Body by Finite Element Method

Since metros are high capacity, fast and large in size compared to other urban rail vehicles, the importance of body strength is very critical. In this study, a four-car metro system was designed and structural analyses of the vehicle body were carried out using the finite element method according to EN 12663-1 standard. Structural analyses were performed under three different conditions. the total mass of the 22.7 m long vehicle with all its equipment was 35000 kg, and the total passenger mass was calculated as 27020 kg based on the presence of 8 passengers per square meter, and the total total mass was taken as 62020 kg. Various sizes of SUS304 stainless steel profiles and sheet materials have been selected for the body carrier skeleton system of the vehicle. In the analysis; vertical loads were made on the passenger side of the vehicle body and horizontal compression loads were made on the bumper areas and maximum stress and displacement amounts were determined. It was found that in the passenger compartment of the car body, the maximum amount of stress in vertical loads is below the yield stress, but in the case of compression loading in the bumper area, the maximum stress is above the yield stress. In order to provide the necessary stress conditions for the design of the buffer zone and its surroundings, solution proposals have been made to revise the design.

Parameters Optimization of an Intermediate Frequency Isolated SiC Power DC-DC Converter

To improve the lightweight level of auxiliary converters for urban rail vehicles, full SiC intermediate frequency auxiliary converters have become a trend. Aiming at its core component, a full SiC intermediate frequency isolated DC-DC converter using Boost + LLC topology is studied in this paper. The working principle and characteristics of the converter are analyzed in detail. Based on the operating characteristics of the LLC resonant converter and the realization mechanism of soft switching, an optimization design method of the resonant parameters is proposed, which can make LLC resonant converters exhibit the characteristics of DC transformers and realize soft switching in the full load range. Considering the power losses of the converter and the voltage stress of SiC MOSFET, the design method of the intermediate bus voltage is given. Finally, the correctness of the parameter design method is verified by simulation and experiment, and the performance of the full SiC intermediate frequency isolated DC-DC converter is analyzed. When the input voltage is 1500V and the output power is 15kW, the efficiency of the converter reaches 96.21%. Compared with the Si intermediate frequency isolated DC-DC converter, the power density is improved by 80.62%.

Vehicle-to-grid application with hydrogen-based tram

Hydrogen is acquiring a central role in energy uses, aiming to support and, then, replace conventional sources. Innovative smart-grids are based on new concepts of energy production and distribution, focus of research studies and preliminary prototypes. In this field, fuel cell-based vehicle-to-grid applications can be a useful system as a back-up power device during energy oscillations and as a transportation mode, especially in public service. In the present paper, a fuel cell hybrid tram is numerically tested, modelling dynamically each main component, with the aim to operate as a power and heat supplier, during the night, and as an urban light rail vehicle, during the day. The fuel cell model is developed, highlighting the principal elements of stack, auxiliary and heat-water management sub-systems. Performance improvements, such as regenerative braking and cogenerative processes, are taken into account, conceptualizing an innovative cooling method. In addition, a 3D CAD model is built to define a suitable layout for the hybrid powertrain, following safety guidelines. In the simulation campaigns, encouraging results are achieved for the case study analysed: for daily operations, the fuel cell-based powertrain provides approximately 2 MWh, consuming 108 kg of hydrogen (48 kg in vehicle-to-grid mode and 60 kg in mobility mode) and reaching an overall efficiency of approximately 43%. In addition, during vehicle-to-grid mode, the tram supplies thermal power capable of warming up at 45 °C almost 0.2 kg/s of tap water on average, obtaining a cogenerative efficiency that exceeds 60%. The promising performance achieved could represent the first steps of the proof of feasibility for this innovative technology.

A Study on Evaluation index for Current Collecting Quality of Shoe Rail Power Supply System

The evaluation of current collecting quality of the third rail power supply system is a comprehensive and complex problem, which shall take overall factors into consideration such as technology development, economical efficiency, correlativeness among each index and accessibility of these indexes. This paper not only introduces the types and advantages of the third rail current collecting system, but also its procedure for establishing the evaluation index and evaluation standard. Then this paper puts forward some constructive suggestions on how to evaluate the current collector and the third rail current collecting quality in view of the evaluation index of Pantograph-OCS system and the experience of domestic urban rail vehicle operations.

A Supercapacitor-Based Interior Permanent Magnet Synchronous Motor Drive Using Intelligent Control for Light Rail Vehicle

A supercapacitor (SC)-based interior permanent magnet synchronous motor (IPMSM) drive including the speed tracking of a specific velocity profile and the charging of the SC is developed in this study to emulate the operation of an urban light rail vehicle (LRV). In the SC-based IPMSM drive, the motoring mode to emulate the LRV speed tracking control and the charging mode for the charging of the SC are both designed. In the motoring mode, a field-oriented controlled (FOC) IPMSM drive system is developed to emulate the speed control of an LRV. In the charging mode, the constant current and constant voltage (CC–CV) charging strategy is developed for the charging of the SC. Moreover, the above two modes use the same inverter and coordinate transformations to reduce the design complexity. Furthermore, in order to test the performance of SC, the speed command of the emulated LRV is obtained using a specific testing driving cycle. The design objective is for fast charging of SC being able to provide enough energy for the emulated LRV to operate a full testing driving cycle. In addition, to improve the transient speed response of the emulated LRV, a Chebyshev fuzzy neural network (CheFNN) intelligent speed controller is proposed. Finally, the simulation and experimental results are given to demonstrate the effectiveness of the developed CC–CV charging strategy for the SC and the proposed CheFNN speed controller for the emulated LRV.

Design and Numerical Simulation of a Ball Cutting Type Energy Absorber Device

This paper is verified by numerical simulation and experiment. Based on the principle of energy absorption in metal cutting process, this paper presents a new type of energy absorption structure, which can improve the collision performance of urban rail vehicles. The structure is composed of solid energy absorption tube, hard ball, anti-crawling board and mounting board. Based on the nonlinear dynamic simulation theory and the explicit algorithm of finite element software ABAQUS, the finite element model of the structure of the cutting type energy absorber was established, and the energy absorption process was simulated. Based on the verified simulation model, the influences of the design parameters such as the cutting depth and the number of balls on the energy absorption process are analyzed. It is found that the design parameters affect the cutting force and energy absorption, and the structure has a good energy absorption effect during the collision.

Research on energy management of vehicle-mounted PV / energy storage dc micro-grid

The application of multi-energy systems in urban rail vehicles have attracted increasing attention. However, the existing studies were mainly focused on high-voltage systems, but rarely on low-voltage multi-energy systems. Based on the world’s first hybrid fuel cell / supercapacitor 100%-low-floor tram, a model of vehicle-mounted PV / energy storage low-voltage DC micro-grid is proposed for the train’s 24V DC loads. Moreover, an energy management strategy based on Fuzzy control is proposed to achieve the sufficient consumption of PV power and the reasonable SOC distribution of the battery. The calculation results show that the proposed low-voltage multi-energy system can meet the load demand and the battery constraints, and the PV utilization rate is as high as 99.8%.

Anomaly Detection and Attack Classification for Train Real-Time Ethernet

Real-time Ethernet has been applied to train control and management system (TCMS) of 250km/h Fuxing Electric Multiple Units (EMUs) and some urban rail vehicles. The openness of the Ethernet communication protocol poses a risk of intrusion attacks on the train communication network. It is, therefore, necessary that a safety protection technology is introduced to the train communication network based on real-time Ethernet. In this paper, a train communication network intrusion detection system based on anomaly detection and attack classification is proposed. Firstly, the paper built an anomaly detection model based on support vector machines (SVM). The particle swarm optimization-support vector machines (PSO-SVM), and genetic algorithm-support vector machines (GA-SVM) optimization algorithms are used to optimize the kernel function parameters of SVM. Secondly, the paper built two attack classification models based on random forest. They are iterative dichotomiser3 (ID3) and classification and regression tree (CART). And then, the built intrusion detection and attack classification model is tested by using the public data set knowledge discovery and data mining-99(KDD-99) and the data set of the simulation train real-time Ethernet test bench. PSO-SVM improves the intrusion detection accuracy from 90.3% to 95.75%, GA-SVM improves the detection accuracy from 90.3% to 95.85%. The training time of the PSO-SVM algorithm was higher than that of the GA-SVM algorithm, and much higher than that of the SVM, without optimization. Both ID3 and CART models are verified valid in the attack classification, while the ID3 algorithm obtained 100% accuracy on the training set, and only 32.89% accuracy on the test set, ID3 has a poor classification accuracy of the data outside of the training set. Also, the classification time is very long for ID3 compared with CART. So the comprehensive experimental results show that the intrusion detection system of train real-time Ethernet can use the GA-SVM model for detection of abnormal data. After passing the normal data, the CART model can be used to distinguish between the types of attacks to better complete subsequent responses and operations. Compared with the anomaly detection model based on SVM, the proposed model improves intrusion detection accuracy. And the proposed attack classification algorithm based on CART can improve the computing speed while ensuring the precision of classification.