Key Technologies for Intelligent Control of Heavy-Haul Trains Focusing on Safe and Efficient Operation
Considering the developmental trends towards automation and intelligence in China's heavy-haul railways, as well as the severe challenges that the continuous growth in heavy-haul railway transportation demands poses to existing train operational control, this paper presents the current research...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Control and Information Technology
2024-08-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2024.04.018 |
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| Summary: | Considering the developmental trends towards automation and intelligence in China's heavy-haul railways, as well as the severe challenges that the continuous growth in heavy-haul railway transportation demands poses to existing train operational control, this paper presents the current research status of key technologies for the intelligent control of heavy-haul trains and analyzes pressing issues and future trends. Firstly, regarding the longitudinal dynamics modeling of trains, existing studies primarily focus on mechanism modeling and analysis under single environment and fixed conditions, making it difficult to accurately characterize the spatio-temporal variability of both interior and exterior parameters during train operation. Therefore, this paper recommends considering dynamic effects not captured by existing mechanism models and exploring order reduction equivalency in future research. Secondly, the strong nonlinear coupling characteristics between cars in long-consist trains and the impact of air braking characteristics on longitudinal impulses during train operation, still pose significant challenges for optimizing the control of heavy-haul trains. Drawing from multi-vehicle cooperative control techniques for high-speed trains, research into the distributed cooperative control of heavy-haul trains with multiple locomotives is of great significance, due to its active suppression of longitudinal impulses. Finally, this paper analyzes new opportunities in the field of train control, incorporating emerging technologies such as data-driven approaches, artificial intelligence algorithms, and multi-source information fusion. Additionally, it discusses the establishment of coupled simulation platforms and evaluation systems as potential means for the effective analysis, evaluation, and optimization of operational safety for heavy-haul trains. |
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| ISSN: | 2096-5427 |