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2024 | OriginalPaper | Buchkapitel

Mathematical Model of Adaptive Optimal Allocation for the Whole Process of Driving Through No. 18 Non-crossing Crossover Considering Special Sections

verfasst von : Ganghui Zhao, Ying Wang, Xiaoqiang Chen, Yixuan Wang

Erschienen in: Proceedings of the 6th International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT) 2023

Verlag: Springer Nature Singapore

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Abstract

With the large-scale construction and the requirement of speed increase of high-speed railway in China, non-crossing crossover has been widely used in high-speed railway catenary. In order to satisfy the requirements of smooth operation of the line, a model of No. 18 non-crossing crossover based on the whole running process is proposed. Based on the whole process of driving through No. 18 non-crossing crossover, the operating principle of No. 18 non-crossing crossover is introduced, the whole model of No. 18 non-crossing crossover composed of line center and contact line model is established, the process of driving through two special sections of No. 18 non-crossing crossover initial contact area and contour area is studied, the influence of special section on the model of no-crossing crossover is considered, and the special section model of No. 18 non-crossing crossover is established. Based on the laboratory platform, the software of No. 18 non-crossing crossover is developed, and the model is validated by using the measured data of high-speed field of Ningdong Station from Yinchuan to Zhongwei of Yinlan Passenger Dedicated. The calcu-lation results show that the proposed model has the characteristics of validity, accuracy and real-time, and is suitable to the calculation of No. 18 non-crossing crossover in various situations.

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Metadaten
Titel
Mathematical Model of Adaptive Optimal Allocation for the Whole Process of Driving Through No. 18 Non-crossing Crossover Considering Special Sections
verfasst von
Ganghui Zhao
Ying Wang
Xiaoqiang Chen
Yixuan Wang
Copyright-Jahr
2024
Verlag
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-99-9319-2_3