Prediction Model and Verification of Wheel Wear in High-speed Trains

2016 ◽  
Vol 52 (2) ◽  
pp. 144 ◽  
Author(s):  
Peng HAN
Keyword(s):  
Prediction Model ◽  
High Speed ◽  
Wheel Wear ◽  
High Speed Trains

Automatic Prediction Model of Ground Vibration for High-Speed Trains

2015 ◽  
Vol 764-765 ◽  
pp. 644-648
Author(s):  
Yit Jin Chen ◽  
Chi Jim Chen
Keyword(s):  
Prediction Model ◽  
High Speed ◽  
Influence Factors ◽  
Ground Vibration ◽  
Support Vector ◽  
Vibration Level ◽  
Vibration Data ◽  
High Speed Trains ◽  
Train Speed ◽  
Ground Condition

This paper presents an automatic prediction model for ground vibration induced by Taiwan high-speed trains on embankment structures. The prediction model is developed using different field-measured ground vibration data. The main characteristics that affect the overall vibration level are established based on the database of measurement results. The influence factors include train speed, ground condition, measurement distance, and supported structure. Support vector machine (SVM) algorithm, a widely used prediction model, is adopted to predict the vibration level induced by high-speed trains on embankments. The measured and predicted vibration levels are compared to verify the reliability of the prediction model. Analysis results show that the developed SVM model can reasonably predict vibration level with an accuracy rate of 72% to 84% for four types of vibration level, including overall, low, middle, and high frequency ranges. The methodology in developing the automatic prediction system for ground vibration level is also presented in this paper.

Influence of motor harmonic torque on wheel wear in high-speed trains

2019 ◽  
Vol 234 (1) ◽  
pp. 32-42
Author(s):  
Yayun Qi ◽  
Huanyun Dai
Keyword(s):  
High Speed ◽  
Dynamic Performance ◽  
Harmonic Component ◽  
Wear Depth ◽  
Vertical Force ◽  
Wheel Wear ◽  
High Speed Trains ◽  
Train Speed ◽  
Lateral Creep ◽  
Creep Force

With the increase of train speed, the harmonic torque of the traction motor of a high-speed train is not a negligible source of excitation. In order to explore the influence of the harmonic torque of the motor on wheel wear, a high-speed EMU vehicle model was established based on the multibody dynamics theory. FASTSIM was used to calculate the wear parameters, and the Zobory wear model was used to calculate the depth of the wheel wear. The influence of the harmonic torque of the motor on the wear parameters and wear depth of high-speed trains under straight and curve conditions is calculated, respectively. The simulation results show that the harmonic torque has a large influence on the wheel rail vertical force and the longitudinal creep force and has little influence on the lateral creep force. With the 30% harmonic torque, the wheel rail vertical force increases by 7.6%, the longitudinal creep force increases by 15%, and the lateral creep force increases by 4%. The amplitude of the longitudinal creepage increases by 14.2% when the harmonic torque is 10%, and increases by 34.4% when the harmonic torque is 30%. When the harmonic torque increases, the wheel wear depth increases, the 10% harmonic torque increases by 3% and the 30% harmonic torque increases by 8%, and the increase of the motor harmonic component accelerates the wheel wear. At the same time, small longitudinal positioning stiffness can help to reduce the influence of the harmonic torque, and the selection of the longitudinal positioning stiffness needs to consider the dynamic performance of the vehicle.

scholarly journals Independently Rotating Wheels with Induction Motors for High-Speed Trains

2011 ◽  
Vol 2011 ◽  
pp. 1-7 ◽  
Author(s):  
B. Liang ◽  
S. D. Iwnicki
Keyword(s):  
Induction Motor ◽  
High Speed ◽  
Dynamic Control ◽  
Feedback Mechanism ◽  
Wheel Wear ◽  
Field Orientation ◽  
Railway Vehicles ◽  
Stability Performance ◽  
Field Orientation Control ◽  
High Speed Trains

Railway vehicles with conventional wheelsets often experience problems of lateral instabilities or severe wear when running at high speed. The use of an independently rotating wheelset (IRW) can potentially eliminate the cause of wheelset hunting and reduce wheel wear as the mechanical feedback mechanism causing the problem is decoupled. This paper presents an investigation into the design of a novel induction motor configuration and controller for IRW in order to provide the stability required to satisfy the performance requirements for railway vehicles. A computer model of the mechanical and electrical parts of the system was developed. Simulation and experiments of the wheelsets with active driving motor control have demonstrated that a wheelset with independently driven wheels has a good stability performance over a traditional wheelset. Controllers with indirect field orientation control for dynamic control of an induction motor have shown to be suitable for this application in both its response and its controllability.

scholarly journals Improved Generalized Predictive Control for High-Speed Train Network Systems Based on EMD-AQPSO-LS-SVM Time Delay Prediction Model

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Xiangyu Kong ◽  
Tong Zhang
Keyword(s):  
Control System ◽  
Time Delay ◽  
Prediction Model ◽  
Least Squares ◽  
Predictive Control ◽  
High Speed ◽  
Generalized Predictive Control ◽  
Safe Operation ◽  
High Speed Trains ◽  
Delay Prediction

Various control signals of high-speed trains (HSTs) are transmitted through the train communication network. However, the time delay generated during the transmission will cause a significant threat to the stability and safe operation of the train. To overcome the effect of time delay on the train control system, based on empirical mode decomposition (EMD) and adaptive quantum particle swarm optimization (AQPSO) algorithms, a least squares support vector machine (LS-SVM) time delay prediction model is proposed in this paper. The EMD algorithm is used to decompose the time delay sequence into several subsequences, which emphasizes the different local characteristics of the time delay sequence. By improving the calculation method about the successful value of particle iteration, an AQPSO algorithm with adaptive contraction-expansion coefficient is designed to optimize the parameters of different LS-SVM models for predicting each time delay component, which improves the prediction accuracy of network delay. Further, based on actor-critic reinforcement learning algorithm, an improved generalized predictive control method is proposed for the train network system. The actor-critic network is used to predict the future output of the system, and the recursive least squares identification algorithm with the variable forgetting factor is adopted to identify the future system model parameters. Combined with the time delay predicted accurately, the control quantity is sent in advance according to the properly arranged time series, which compensates efficiently the influence of the time delay on the control system. Simulation results show that compared with other control methods, the proposed method has better robustness and stability, which ensures the safe operation of high-speed trains under various working conditions.

Field measurements of the evolution of wheel wear and vehicle dynamics for high-speed trains

2017 ◽  
Vol 56 (8) ◽  
pp. 1187-1206 ◽  
Author(s):  
Huailong Shi ◽  
Jianbin Wang ◽  
Pingbo Wu ◽  
Chunyuan Song ◽  
Wanxiu Teng
Keyword(s):  
Vehicle Dynamics ◽  
High Speed ◽  
Field Measurements ◽  
Wheel Wear ◽  
High Speed Trains

Development and validation of a model for predicting wheel wear in high-speed trains

2017 ◽  
Vol 18 (8) ◽  
pp. 603-616 ◽  
Author(s):  
Gong-quan Tao ◽  
Xing Du ◽  
He-ji Zhang ◽  
Ze-feng Wen ◽  
Xue-song Jin ◽  
...  
Keyword(s):  
High Speed ◽  
Wheel Wear ◽  
High Speed Trains ◽  
Development And Validation
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