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

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

Identyfikatory

DOI

10.5604/01.3001.0016.3132

• Języki publikacji: EN

Abstrakty

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.

Słowa kluczowe

EN

high-speed train; hybrid modeling; speed control; error compensation

PL

pociąg ekspresowy; modelowanie hybrydowe; kontrola prędkości; kompensacja błędów

• Wydawca: Warsaw University of Technology, Faculty of Transport
• Czasopismo: Archives of Transport
• Rocznik: 2023
• Tom: Vol. 66, iss. 2
• Strony: 77--82
• Opis fizyczny: Bibliogr. 22 poz., rys., tab., wykr., wzory

Twórcy

autor

Hou Tao

• Lanzhou Jiaotong University, School of Automation and Electrical Engineering, Lanzhou, China

• https://orcid.org/0000-0002-7511-3013

autor

Tang Li.

• Lanzhou Jiaotong University, School of Automation and Electrical Engineering, Lanzhou, China

• https://orcid.org/0000-0003-4029-9054

autor

Niu Hong-xia

• Lanzhou Jiaotong University, School of Automation and Electrical Engineering, Lanzhou, China

• https://orcid.org/0000-0002-7732-5183

autor

Zhao Tingyang

• Lanzhou Jiaotong University, School of Automation and Electrical Engineering, Lanzhou, China

• https://orcid.org/0000-0002-2410-8732

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)