Electric Multiple Units Research Articles

Comparative study of the current-carrying property of different copper-impregnated carbon skateboards/contact wires

The pantograph-catenary system plays a crucial role in the current acquisition of Electric Multiple Unit. To obtain better carbon skateboard/contact wire matching properties, this study discusses the current-carrying properties of four different copper-impregnated carbon skateboards with chromium-zirconium-copper alloy contact wires at different currents. The test results demonstrate that the CI-D carbon skateboards are able to withstand higher currents with relatively stable electrical contact resistance and have a lower wear rate. According to tribological analysis, adhesive wear was the main wear mechanism of copper-impregnated carbon skateboards under the test conditions, which micro-analysis revealed as oxidized layers over a wide range of small areas. Small amounts of oxide particles and third-body abrasive debris cause abrasive wear on the carbon skateboard surface.

Determining the Gear Design Parameters Which Have Strong Correlation with Gear Volume and Contact Ratio for Helical Gear Design Optimization

The market has a significant demand for low-cost, compact size, extended fatigue life and high load-carrying capacity helical gears. One way to manufacture such gears is by minimizing gear volume and maximizing contact ratio. Most researchers focus on gear design optimization, but minimal study has been conducted to identify design variables that significantly impact gear volume and contact ratio. Hence, it is crucial to determine gear design parameters that strongly correlate with gear volume and contact ratio beforehand. A single-stage helical gear train of local electric multiple units (EMU) is used as the gear model, and the calculations are done based on ISO 6336. Seven parameters have been chosen as independent variables; module, number of teeth of pinion, gear ratio, helix angle, tooth thickness factor, normal pressure angle and addendum factor. Graphs of total gear volume and contact ratio against independent variables are plotted to examine their relationship. The results indicate that normal module, number of teeth of the pinion, and gear ratio strongly correlate with the total gear volume. Meanwhile, the number of teeth of pinion, helix angle, tooth thickness factor, normal pressure angle and addendum factor strongly correlate with contact ratio. Therefore, these design parameters must be considered to improve the accuracy of the gear design optimization model, which aims to optimize gear volume and contact ratio.

Bridge-Borne Noise Induced by High-Speed Freight Electric Multiple Units: Characteristics, Mechanisms and Control Measures

The high-speed freight electric multiple unit (EMU) is one of the important development directions for railway freight transportation. To investigate the bridge radiation noise induced by the freight EMU, a noise prediction model consisting of the containers–vehicle–track–bridge dynamic model, finite element model, and boundary element model are established and validated. Through simulation, the bridge radiation noise under different train loading conditions is compared, and the noise radiation mechanism is revealed. Moreover, the noise reduction effect of the noise wall is studied, and the influences of noise wall heights and sound absorption materials are investigated. Results indicate that the bridge sound power and the sound pressure levels (SPLs) of near-field points increase slightly with train loads in the frequency range below 20 Hz and above 125 Hz, with a maximum increase of about 6.8 dB. The structure resonance, intense local vibration, and high acoustic radiation efficiency cause strong bridge radiation noise. The noise wall can realize a good overall noise reduction effect in the sound shadow zone; nevertheless, SPLs increased in areas between the bridge and the noise wall. The ground reflection affects the superposition of transmitted, reflected, and diffracted sound waves, which causes nonlinear relationships of noise reduction effects with the noise wall height. From the perspective of human hearing sensitivity, the loudness levels of typical field points increase with the frequency in the range of 20~80 Hz, and SPLs below 25 Hz are less than the threshold of hearing. Setting the noise wall can effectively reduce the loudness levels, and the reduction effect increases with the noise wall height.

Extended Pantograph–Catenary Arc Modeling and an Analysis of the Vehicular-Grounding Electromagnetic Transients of Electric Multiple Units

As the operating speed of electric multiple units (EMUs) in high-speed railways increases, pantograph–catenary (PC) detachment arcing occurs frequently. The resulting vehicular-grounding electromagnetic transients are related to the dynamic characteristics of the arc length. During large detachment, the processes of arc extinction and arc reignition may occur, resulting in more severe train body (TB) over-voltages and adverse effects on some vehicular electronic devices. As an extension of the previous works, this paper aims to establish a suitable PC arc model to examine the TB transient voltages. To begin with, the arc length dynamic characteristics are reasonably analyzed to deduce the relationship between the detachment distance and the arc length via the chain arc model. Then, the dynamic characteristics of the arc length are introduced, and an arc modeling scheme is proposed to elaborate the vehicle-grid electric power model for EMUs encountering various arcing scenarios. Based on this, the transient over-voltages are analyzed, accounting for both the arc extinction and arc reignition, as well as the mutual influences of multiple detachments in a short time. The influential factors, including arc length characteristics, phase angle, excitation inductance, and grounding parameters, are also involved in the performed analyses.

Integrating MBD with BOM for consistent data transformation during lifecycle synergetic decision-making of complex products

Model-based definition (MBD) can be applied to normalized define and associate the whole lifecycle data of complex products by a three-dimensional (3D) digital model, which can further provide single data source for bill of material (BOM) transforming of different lifecycle stages. Therefore, a promising application combining MBD and BOM is to ensure the accuracy and completeness of information during various BOM transformation, and to provide consistent and reliable data support for lifecycle synergetic decision-making. However, the studies in the above field are facing many challenges. For example, the research and application of MBD in the whole lifecycle is still in its infancy. MBD and BOM are studied separately, and the overall solution that integrates these two pillars for lifecycle synergetic decision-making is almost vacant. A novel approach for consistent lifecycle data transformation is proposed to address these challenges. First, an overall conceptual framework is developed to show how the approach can be implemented. Second, a unified lifecycle data representation method with the MBD main-domain dataset is proposed. Third, based on the single data source from MBD dataset, xBOM multi-view transforming are realised by designing a set of mapping models and rules. Finally, an applicable scenario for an electric multiple units (EMU) bogie is presented to illustrate the effectiveness of the proposed approach. The result shows that the proposed approach can provide significant potential for industrial practitioners to carry out synergetic and optimal decision-making in the whole lifecycle management processes.

Signed-data reinforced observer-based fault diagnosis for virtually-coupled electric multiple units trains

Virtual coupling has been recognized as a promising yet challenging technology for the next generation of train control systems. As a mean of guaranteeing the safety of closer-running of virtually-coupled electric multiple units (EMU) trains, fault detection and diagnosis play a critical role in perceiving abnormal running conditions. This paper develops a new signed-data reinforced observer-based technique for dealing with actuator faults’ detection and diagnosis for virtually-coupled EMU trains. The introduction of novel signed-data reinforcement technique ensures that unbiased fault diagnosis can be guaranteed with any regressor vector composed of control signals on EMU trains. Fault detection and diagnosis observers, together with fault alarming principle, information transmission coding strategy are elaborated using Lyapunov stability theorem. Simulation results are given to demonstrate the effectiveness of proposed algorithm.

Research on the evolution law of dynamic performance of CR400BF EMU train based on stochastic dynamics simulation

PurposeThis paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).Design/methodology/approachUsing the dynamic simulation based on field test, stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers were tested. Stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to research the evolution law with running mileage of dynamic index of CR400BF EMU.FindingsThe results showed that stiffness and damping coefficient subjected to normal distribution, the mean and variance were computed and the evolution law of stiffness and damping coefficient with running mileage was obtained.Originality/valueFirstly, based on the field test we found that stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers subjected to normal distribution, and the evolution law of stiffness and damping coefficient with running mileage was proposed. Secondly stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to the research to the evolution law with running mileage of dynamic index of CR400BF EMU.

Research on the influence of power frequency magnetic field of pantograph on pacemaker wearers' health in high-speed EMU.

When the popular means of transportation-high-speed trains meet the increasing rate of pacemaker implantation year by year, the research on the magnetic field environment on the health of pacemaker wearers in the carriage becomes an urgent problem. In this work, models of an electric multiple unit carriage with a pantograph as well as passengers with pacemakers were built by using COMSOL Multiphysics software. The B, Ein and Jin of human heart and other tissues, and the induced voltage (Vin) at the pacemaker electrode were calculated under the pantograph operating condition, so as to assess the effect of its magnetic field on the health of pacemaker wearers. The results showed that Bmax in the carriage without passengers is 121.246 μT, occurs near the window. In the carriage, the Bmax, Ein max and Jin max of heart and body, Vin at the pacemaker electrode of the passenger next to the window are greater than that in the middle of the carriage. The Bmax, Ein max and Jin max of passengers' heart are 11.301μT, 1.613mV/m and 139.030μA/m2, respectively. The Bmax, Ein max and Jin max of passengers' body are 12.597μT, 0.788mV/m and 75.299μA/m2, respectively. The maximum value of Vin at the tip of the pacemaker electrode of the passengers' is 0.048mV. The Bmax, Ein max in all tissues of passengers are much smaller than the basic limits of electromagnetic exposure to the public set by the International Commission on Non-Ionizing Radiation. Vin at the electrode tip of passengers' pacemakers are less than the perception sensitivity set by the International Organization for Standardization. This work illustrated that the magnetic field generated by the pantograph is within the recognized accepted limits for passengers with pacemakers, but we still recommended that passengers wearing pacemakers should stay as far away from windows as possible.

A method for modifying octagonal Goodman–Smith fatigue limit diagram

PurposeIn order to extend the application of the original octagonal Goodman–Smith fatigue limit diagram, which is commonly used for the evaluation of structure fatigue stress in engineering, a modification of it is proposed for the structure made of S355 steel (commonly used in high-speed electric multiple units (EMUs) bogie frame).Design/methodology/approachThe modification is made based on Deutscher Verband für Schweißen und verwandte Verfahren e. V. (DVS) 1612 standard and the γ-P-S-N curve, with consideration of the fatigue evaluation requirements of different survival rates and confidence levels. The verification of the modification is performed for three welded joints and for the comparison with the experimental data.FindingsThe results indicate that the design survival rate, the design safety margin and the fatigue stress evaluation of welded joint types are all improved by using the modified diagram.Originality/valueThere are relatively few studies on modifying octagonal Goodman–Smith fatigue limit diagram. In this paper, a modified diagram is proposed and applied in order to ensure the safety and durability of key welded structures of rail vehicles.

A survey on countermeasures of railway vehicle stability decrease caused by the evolution of hollow-worn wheels

With the problem that the lateral vibration acceleration of the frame of a certain type of Electric Multiple Units (EMU) gradually approaches the limit value as the running mileage increases, the tracking test was conducted on the whole vehicle’s wheel tread wear and the frame’s vibration response. It was found that as the tread hollow-worn increased, the vehicle stability would deteriorate. In order to improve vehicle stability, an optimisation method of EMU stability is proposed based on controlling the evolution of hollow-worn wheels. The results show that after optimisation by this method, the hollow-worn state of the wheel tread is significantly improved; the equivalent conicity of the worn wheel is reduced by 16.39%, and the maximum lateral vibration acceleration of the frame is reduced by 32.02%, so the vehicle stability is also significantly improved; meanwhile, the ride comfort and safety of the vehicle still meet the requirements of the standard.

Matlab-Simulink Simulation Model of Electric Multiple Unit (EMU) Series ŽS 413/417 in Traction and Electric Braking Mode

Matlab-Simulink Simulation Model of Electric Multiple Unit (EMU) Series ŽS 413/417 in Traction and Electric Braking Mode

Failure Characterization of Al-Zn-Mg Alloy and Its Weld Using Integrated Acoustic Emission and Digital Image Techniques

The three-point bending damage process of an A7N01 aluminum alloy body material and weld seam in an electric multiple unit train was monitored using acoustic emission (AE) and digital image technology. The AE signal characteristics of static load damage to the aluminum alloy and weld seam were studied using the AE signal parameter and time–frequency analysis. Based on the observation of the microstructure and fracture morphology, the source mechanism of AE signals was analyzed. The experimental results indicate that AE energy, centroid frequency, and peak frequency are effective indices for predicting the initiation of cracks in A7N01 aluminum alloy and weld seams. The digital image monitoring results of the notch tip damage evolution of aluminum alloy samples confirmed the predictions based on AE energy, centroid frequency, and peak frequency for crack initiation. The AE signal source mechanism revealed that the differences in AE characteristics between the base material and weld seam can be attributed to microstructure variations and fracture modes. In summary, the AE technique is more sensitive to changes in the fracture mode and can be utilized to monitor the damage evolution of welded structures.

Defect Identification Method of Cable Termination based on Improved Gramian Angular Field and ResNet

Background: This paper proposes a defect identification method for vehicle-mounted cable terminals in electric multiple units (EMUs) based on the improved Graham angle field and residual network to address the issue of low recognition accuracy caused by the lack of partial discharge (PD) and identification data for Ethylene Propylene Rubber (EPR) cable terminal defects. Methods: The improved Gramian angular field (IGAF) characteristic transformation method was used to transform the PD one-dimensional time-series signal into a two-dimensional one after cable terminals with four common insulation defects were constructed, and a PD detection platform was built. Finally, an anti-aliasing downsampling module and attention mechanism were added to the residual network ResNet101 model. The Center loss and Softmax loss functions were integrated to increase accuracy for training and recognition classification. Topological feature images improved the distinguishability of defect categories. Results: The test results showed that the diagnostic method has an accuracy rate of 97.3% for identifying PD at the cable terminal. Conclusion: The proposed diagnosis model has higher recognition accuracy and better balance than other conventional fault diagnosis methods, making it suitable for diagnosing high-voltage cable faults in EMU trains.

Classification of Partial Discharge in Vehicle-Mounted Cable Termination of High-Speed Electric Multiple Unit: A Machine Learning-Based Approach

This paper presents a machine learning-based approach to identify and separate partial discharge (PD) and two typical pulse interference (PI) signals in the vehicle-mounted cable terminations of high-speed electric multiple units (EMUs). First, a test platform was established to capture PD and two typical PI signals in these terminations. The acquired signals were then processed using the square envelope method to extract feature parameters, such as the rise time proportion, the left–right symmetry, and the upper–lower symmetry. PD signal classification was carried out on these signals, utilizing waveform parameters derived from a hierarchical clustering algorithm. The results validate that the extracted feature components effectively classify and separate PD and two typical PI signals in the vehicle-mounted cable terminations of high-speed EMUs.

Research on a Fault Diagnosis Method for the Braking Control System of an Electric Multiple Unit Based on Deep Learning Integration

A fault diagnosis method based on deep learning integration is proposed focusing on fault text data to effectively improve the efficiency of fault repair and the accuracy of fault localization in the braking control system of an electric multiple unit (EMU). First, the Borderline-SMOTE algorithm is employed to synthesize minority class samples at the boundary, addressing the data imbalance and optimizing the distribution of data within the fault text. Then, a multi-dimensional word representation is generated using the multi-layer bidirectional transformer architecture from the pre-training model, BERT. Next, BiLSTM captures bidirectional context semantics and, in combination with the attention mechanism, highlights key fault information. Finally, the LightGBM classifier is employed to reduce model complexity, enhance analysis efficiency, and increase the practicality of the method in engineering applications. An experimental analysis of fault data from the braking control system of the EMU indicates that the deep learning integration method can further improve diagnostic performance.

Simulations of electric multiple unit series 413/417 drives on the electrified tracks of "Serbian Railways"

In the paper, the Matlab-Simulink model of simulation of operation of the ŽS 413/417 series electric multiple unit (EMU) in traction and braking mode is exposed where changes are observed: stator currents of three-phase traction motors, traction electric motor speeds and electric multiple unit, electromagnetic torque on the rotor shaft of the traction electric motor and DC bus voltage. The model allowed review of the listed parameters for: different allowed values of contact network voltage and total voltage distortion at the place of connection of the electric multiple unit to the contact network, different mechanical loads of electric multiple unit and traction electric motor and different train speeds and rotation of traction electric motors. Appropriate conclusions were made through the analysis of the simulation results obtained.

Design of High-power Density and High-frequency Transformers for Auxiliary Power Supply System in Electric Multiple Units

Design of High-power Density and High-frequency Transformers for Auxiliary Power Supply System in Electric Multiple Units

Fine Tuning of On-Board Traction Converters for High-Speed Electric Multiple Units at Depot

Fine Tuning of On-Board Traction Converters for High-Speed Electric Multiple Units at Depot

Study on Oil-Gas Separation Characteristics of Gearbox Sealing System of High-Speed Electric Multiple Unit

Based on the discrete phase model (DPM) and droplet-wall collision model, this paper analyzes the oil-gas separation characteristic and sealing performance of a gearbox sealing system. The results show that the airflow drag force and oil droplet inertia force affect the oil-gas separation efficiency of the sealing system. Furthermore, larger oil droplet diameter leads to a higher separation efficiency and lower outlet back pressure reduces the separation efficiency of smaller diameter oil droplet and increases the separation efficiency of larger diameter droplet. For oil droplet with an intermediate diameter, the separation efficiency first decreases and then increases with the reduction in back pressure.

Development of a forward design method for train airtightness: A case study of a metro express line

Focusing on metro express lines, this study develops a train airtightness forward design method by deconstructing whole-vehicle pressure change and dynamic sealing index requirements into key airtight component static sealing indices. This is achieved through the utilization of theoretical calculations, simulation calculations, laboratory tests, and field tests. Firstly, a research framework for the train airtightness forward design method is established. Subsequently, a sealed train is manufactured based on existing capabilities, and the following research is conducted: 1) Establishment of a conversion formula between key airtight component static sealing indices and the theoretical whole-vehicle static sealing index. 2) Examination of the theoretical weight relationship between key airtight components and the whole-vehicle theoretical static sealing performance, revealing that the doors and the carriage body each contribute to almost 50 % of the entire train's static sealing performance. 3) Investigation into the relationship between whole-vehicle theoretical and actual static sealing indices, revealing that test values for head/tail car pressure retention duration and static sealing index are 16 % below theoretical values, while those for the middle car are 13 % lower than the theoretical values. 4) Assessment of the validity of current standards. 5) Establishment of a calculation method for the relationship between whole-vehicle dynamic and static sealing indices, discovering that the whole-vehicle dynamic sealing index is 0.034–0.081 times the whole-vehicle static sealing index. 6) Development of a Computational Fluid Dynamics (CFD) simulation method to calculate metro trains' external wall pressure, which is validated through real-vehicle test data. Finally, within this framework, the train airtightness forward design method is formulated by determining the unknown relationships among airtightness parameters, standard indices, and simulation methods. Importantly, the forward airtightness design process and method established in this study are not limited to metro trains alone. They also serve as valuable references for airtightness research and development in various other products with similar requirements, including locomotives, electric multiple units, high-speed trains, and maglev trains.