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Research on speed control of high speed trains based on hybrid modeling

Hou Tao, Tang Li., Niu Hong-xia, Zhao Tingyang

Archives of Transport

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2023

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Vol. 66, iss. 2

77--82

EN

With the continuous improvement of train speed, the automatic driving of trains instead of driver driving has become the development direction of rail transit in order to realize traffic automation. The application of single modeling methods for speed control in the automatic operation of high-speed trains lacks exploration of the combination of train operation data information and physical model, resulting in low system modeling accuracy, which impacts the effectiveness of speed control and the operation of high-speed trains. To further increase the dynamic modeling accuracy of high-speed train operation and the high-speed train's speed control effect, a high-speed train speed control method based on hybrid modeling of mechanism and data drive is put forward. Firstly, a model of the high-speed train's mechanism was created by analyzing the train's dynamics. Secondly, the improved kernel-principal component regression algorithm was used to create a data-driven model using the actual operation data of the CRH3 (China Railway High-speed 3) high-speed train from Huashan North Railway Station to Xi'an North Railway Station of "Zhengxi High-speed Railway," completing the mechanism model compensation and the error correction of the speed of the actual operation process of the high-speed train, and realizing the hybrid modeling of mechanism and data-driven. Finally, the prediction Fuzzy PID control algorithm was developed based on the natural line and train characteristics to complete the train speed control simulation under the hybrid model and the mechanism model, respectively. In addition, analysis and comparison analysis were conducted. The results indicate that, compared to the high-speed train speed control based on the mechanism model, the high-speed train speed control based on hybrid modeling is more accurate, with an average speed control error reduced by 69.42%. This can effectively reduce the speed control error, improve the speed control effect and operation efficiency, and demonstrate the efficacy of the hybrid modeling and algorithm. The research results can provide a new ideal of multi-model fusion modeling for the dynamic modeling of high-speed train operation, further improve control objectives such as safety, comfort, and efficiency of high-speed train operation, and provide a reference for automatic driving and intelligent driving of high-speed trains.

2

Research on speed control of high-speed train based on multi-point model

Hou Tao, Guo Yang-yang, Niu Hong-xia

Archives of Transport

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2019

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Vol. 50, iss. 2

35--46

EN

The traditional train speed control research regards the train as a particle, ignoring the length of the train and the interaction force between carriages. Although this method is simple, the control error is large for high-speed trains with the characteristics of power dispersion. Moreover, in the control process, if the length of the train is not considered, when the train passes the slope point or the curvature point, the speed will jump due to the change of the line, causing a large control error and reducing comfort. In order to improve the accuracy of high-speed train speed control and solve the problem of speed jump when the train runs through variable slope and curvature, the paper takes CRH3 EMU data as an example to establish the corresponding multi-point train dynamics model. In the control method, the speed control of high-speed train needs to meet the fast requirement. Comparing the merits and demerits of classical PID control, fuzzy control and fuzzy adaptive PID control in tracking the ideal running curve of high-speed train, this paper chooses the fuzzy adaptive PID control with fast response. Considering that predictive control can predict future output, a predictive fuzzy adaptive PID controller is designed, which is suitable for high-speed train model based on multi-point. The simulation results show that the multi-point model of the high-speed train can solve the speed jump problem of the train when passing through the special lines, and the predictive fuzzy adaptive PID controller can control the speed of the train with multi-point model, so that the train can run at the desired speed, meeting the requirements of fast response and high control accuracy.

3

Prediction and validation for the aerodynamic noise of high-speed train power car

Jiang S., Yang S., Wu D., Wen B-Ch.

Transport Problems

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2018

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T. 13, z. 2

91--102

EN

The aerodynamic noise of high-speed train power car was investigated in this article. The full-scale power car was first modeled, and the external steady flow field was computed by a realizable k-ε turbulence model. The aerodynamic noise sources of the power car surface and the external transient flow field were then calculated by broadband noise source model and large eddy simulation (LES) model, respectively. The static pressures on the train surface were obtained from the results of the transient model. Considering the transient flow field, the far-field aerodynamic noise generated by the power car was finally derived from Lighthill-Curle theory. It was validated by means of on-line tests that have been performed along a real high-speed railway line. Through comparisons between simulations and measurements, it is shown that the simulation model gives reliable aerodynamic noise predictions. We foresee numerous applications for modeling and control of the aerodynamic noise in high-speed train.

4

Design of large-scale streamlined head cars of high-speed trains and aerodynamic drag calculation

Wu Z., Yang E., Ding W.

Archives of Transport

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2017

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Vol. 44, iss. 4

89--97

EN

Aerodynamic drag plays an important role in high-speed trains, and how to reduce the aerodynamic drag is one of the most important research subjects related to modern railway systems. This paper investigates a design method for large-scale streamlined head cars of high-speed trains by adopting NURBS theory according to the outer surface characteristics of trains. This method first created the main control lines of the driver cab by inputting control point coordinates; then, auxiliary control lines were added to the main ones. Finally, the reticular region formed by the main control lines and auxiliary ones were filled. The head car was assembled with the driver cab and sightseeing car in a virtual environment. The numerical simulation of train flow field was completed through definition of geometric models, boundary conditions, and space discretization. The calculation results show that the aerodynamic drag of the high-speed train with large-scale streamlined head car decreases by approximately 49.3% within the 50-300 km/h speed range compared with that of the quasi-streamlined high-speed train. This study reveals that the high-speed train with large-scale streamlined head car could achieve the purpose of reducing running aerodynamic drag and saving energy, and aims to provide technical support for the subsequent process design and production control of high-speed train head cars.

5

A framework for categorizing risks in High Speed Train (HST) projects: the example of the first HST in Brazil

Grubisic V., Zagheni E., Asaff Y., Dias A.

Transport Problems

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2015

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T. 10, z. spec.

37--46

EN

High Speed Train projects are exposed to risks of different natures, such as: low participation of private companies in the new railways construction, lack of skilled labor, high technology not available in the internal market, high costs with land acquisition, among others. Such risks if not managed properly can become real problems and compromise the achievement of the project objectives. The risk identification is the process of collection and description of events that can have negative effects on the project. This process should consider the project uncertainty elements in order to generate specific results. In the case of HST projects, examples of uncertainty elements are: politics, economy, environment, human resources and technology. Therefore, this study aims to present a framework for categorizing risks to be used in HST projects. Also, for each category proposed some risk examples are suggested. An overview of the first Brazil HST project is showed and the risk framework is proposed. A discussion on the risks in the first Brazil HST project are presented followed by final conclusions.

ES

Projetos de trens de Alta Velocidade estão expostos a riscos de diversas naturezas como: baixa participação de empresas privadas na construção de novas ferrovias, falta de mão de obra especializada, tecnologia de ponta não disponível no mercado interno, altos custos com aquisição de terrenos, alto impacto ambiental, entre outros. Tais riscos senão forem gerenciados corretamente podem se tornar problemas e comprometer os objetivos do projeto. A identificação de riscos é o processo de coleta e descrição de eventos que podem ter efeitos negativos sobre o projeto. Este processo deve considerar os elementos de incerteza do projeto, a fim de gerar resultados específicos. No caso de projetos de TAV, são exemplos de elementos de incerteza: política, economia, meio ambiente, recursos humanos e tecnologia. Portanto, este estudo tem como objetivo apresentar uma estrutura para classificar os riscos a ser usada em projetos de TAV. Para cada categoria de risco, exemplos de riscos são apresentados. Uma visão geral do primeiro projeto de TAV do Brasil e seus principais riscos são mostrados. Finalmente, tem-se uma discussão sobre os principais resultados do artigo e as conclusões finais.

6

Układy zasilania sieci trakcyjnej dla dużych prędkości na PKP - doświadczenia i wnioski

Szafrański Z.

TTS Technika Transportu Szynowego

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2004

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R. 11, nr 10

25-29

PL

Do 1984 r. maksymalne prędkości osiągane przez pociągi pasażerskie - na odcinkach kilku linii PKP - nie przekraczały 120 km/h (jedynym wyjątkiem były fragmenty linii E20 Poznań-Warszawa, gdzie dozwolona prędkość 130 km/h). Rok 1984, wraz z nowym rozkładem jazdy, przyniósł "rewolucje" w postaci uruchomienia pierwszych pociągów ekspresowych między Krakowem Katowicami a Warszawą przez Centralną Magistralę Kolejową z prędkością maksymalną - na praktycznie całej jej długości - 140 km/h. Umożliwiło to radykalne skrócenie czasu jazdy - z ponad 4 godz. do 2 godz. 30 min. Połączenie to spotkało się z tak wielkim zainteresowaniem pasażerów, że liczba pociągów została wkrótce zwiększona z 2 par do ponad 10 dla każdego kierunku, jednocześnie z wydłużeniem relacji niektórych pociągów poza Kraków, Katowice, Warszawę. Pod koniec lat 80. zwiększono prędkość maksymalną na CMK do 160 km/h, wykorzystując zmodernizowane w latach 70. lokomotywy EP05 i właśnie wprowadzane do eksploatacji EP09.