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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| Format: | Article |
| Language: | zho |
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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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| author | WANG Qingyuan WEI Mi HU Yunqing WANG Jianhua JIANG Fan ZHANG Zhengfang WANG Kaiyun |
| author_facet | WANG Qingyuan WEI Mi HU Yunqing WANG Jianhua JIANG Fan ZHANG Zhengfang WANG Kaiyun |
| author_sort | WANG Qingyuan |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-1a8d09a524f64763beebfb016b0d9588 |
| institution | Kabale University |
| issn | 2096-5427 |
| language | zho |
| publishDate | 2024-08-01 |
| publisher | Editorial Office of Control and Information Technology |
| record_format | Article |
| series | Kongzhi Yu Xinxi Jishu |
| spelling | doaj-art-1a8d09a524f64763beebfb016b0d95882025-08-25T06:57:15ZzhoEditorial Office of Control and Information TechnologyKongzhi Yu Xinxi Jishu2096-54272024-08-0113013968496640Key Technologies for Intelligent Control of Heavy-Haul Trains Focusing on Safe and Efficient OperationWANG QingyuanWEI MiHU YunqingWANG JianhuaJIANG FanZHANG ZhengfangWANG KaiyunConsidering 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.http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2024.04.018heavy-haul trainintelligent operationdynamics modelingoptimize controldata drivenartificial intelligencemulti-source information fusioncoupled simulation platform |
| spellingShingle | WANG Qingyuan WEI Mi HU Yunqing WANG Jianhua JIANG Fan ZHANG Zhengfang WANG Kaiyun Key Technologies for Intelligent Control of Heavy-Haul Trains Focusing on Safe and Efficient Operation Kongzhi Yu Xinxi Jishu heavy-haul train intelligent operation dynamics modeling optimize control data driven artificial intelligence multi-source information fusion coupled simulation platform |
| title | Key Technologies for Intelligent Control of Heavy-Haul Trains Focusing on Safe and Efficient Operation |
| title_full | Key Technologies for Intelligent Control of Heavy-Haul Trains Focusing on Safe and Efficient Operation |
| title_fullStr | Key Technologies for Intelligent Control of Heavy-Haul Trains Focusing on Safe and Efficient Operation |
| title_full_unstemmed | Key Technologies for Intelligent Control of Heavy-Haul Trains Focusing on Safe and Efficient Operation |
| title_short | Key Technologies for Intelligent Control of Heavy-Haul Trains Focusing on Safe and Efficient Operation |
| title_sort | key technologies for intelligent control of heavy haul trains focusing on safe and efficient operation |
| topic | heavy-haul train intelligent operation dynamics modeling optimize control data driven artificial intelligence multi-source information fusion coupled simulation platform |
| url | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2024.04.018 |
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