Research on Multi-Mass Safety Braking Model for Heavy-Haul Trains Based on Random Distribution of Parameters
The virtual coupling technology of trains significantly improves the transportation capacity of railway lines, making it a research hotspot among emerging technologies in the rail transit industry. Its key technical feature lies in a new safety braking model developed based on the concept of "d...
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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.2096-5427.2024.04.006 |
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| author | BAI Jinlei WANG Yue JIANG Fan ZHANG Zhengfang SHI Ke ZHONG Puhua |
| author_facet | BAI Jinlei WANG Yue JIANG Fan ZHANG Zhengfang SHI Ke ZHONG Puhua |
| author_sort | BAI Jinlei |
| collection | DOAJ |
| description | The virtual coupling technology of trains significantly improves the transportation capacity of railway lines, making it a research hotspot among emerging technologies in the rail transit industry. Its key technical feature lies in a new safety braking model developed based on the concept of "dynamic tracking". However, existing research only addresses boundary issues such as emergency braking and minimum headways, lacking applicability in the context of heavy-haul trains, due to the absence of solutions for complex track conditions, strong dispersion in air braking capability, and other unfavorable factors. This paper presents a multi-mass safety braking model specifically for heavy-haul trains, based on the random distribution of parameters, to solve these challenges. Initially, a multi-mass dynamics analysis of trains was conducted based on the topological structure of the virtual coupling system of trains, leading to the establishment of a coupler-draft gear model. Subsequently, a safety braking model for heavy-haul trains was designed by referencing the safety model of the communication-based train control system (CBTC). This model was then utilized for simulation analysis, where technical indexes were evaluated from the perspective of longitudinal dynamics stability, corresponding to different fail-safe measures taken on following trains. In addition, the characteristics of the distribution function for safe braking distances were analyzed in relation to the random variation of typical parameters. Furthermore, verification was performed through the kinematic simulations of trains. Results showed that the proposed model resulted in greatly shortened headways below 1.4 km while improving the safety confidence by about 1 for trains, demonstrating its efficacy in improving both the efficiency and safety of train transportation. |
| format | Article |
| id | doaj-art-2c5276e549f04f6b8ac07f79fe11d690 |
| 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-2c5276e549f04f6b8ac07f79fe11d6902025-08-25T06:57:16ZzhoEditorial Office of Control and Information TechnologyKongzhi Yu Xinxi Jishu2096-54272024-08-01445268496714Research on Multi-Mass Safety Braking Model for Heavy-Haul Trains Based on Random Distribution of ParametersBAI JinleiWANG YueJIANG FanZHANG ZhengfangSHI KeZHONG PuhuaThe virtual coupling technology of trains significantly improves the transportation capacity of railway lines, making it a research hotspot among emerging technologies in the rail transit industry. Its key technical feature lies in a new safety braking model developed based on the concept of "dynamic tracking". However, existing research only addresses boundary issues such as emergency braking and minimum headways, lacking applicability in the context of heavy-haul trains, due to the absence of solutions for complex track conditions, strong dispersion in air braking capability, and other unfavorable factors. This paper presents a multi-mass safety braking model specifically for heavy-haul trains, based on the random distribution of parameters, to solve these challenges. Initially, a multi-mass dynamics analysis of trains was conducted based on the topological structure of the virtual coupling system of trains, leading to the establishment of a coupler-draft gear model. Subsequently, a safety braking model for heavy-haul trains was designed by referencing the safety model of the communication-based train control system (CBTC). This model was then utilized for simulation analysis, where technical indexes were evaluated from the perspective of longitudinal dynamics stability, corresponding to different fail-safe measures taken on following trains. In addition, the characteristics of the distribution function for safe braking distances were analyzed in relation to the random variation of typical parameters. Furthermore, verification was performed through the kinematic simulations of trains. Results showed that the proposed model resulted in greatly shortened headways below 1.4 km while improving the safety confidence by about 1 for trains, demonstrating its efficacy in improving both the efficiency and safety of train transportation.http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2024.04.006heavy-haul trainsafety braking modelvirtual couplingrandom distributionlongitudinal dynamics |
| spellingShingle | BAI Jinlei WANG Yue JIANG Fan ZHANG Zhengfang SHI Ke ZHONG Puhua Research on Multi-Mass Safety Braking Model for Heavy-Haul Trains Based on Random Distribution of Parameters Kongzhi Yu Xinxi Jishu heavy-haul train safety braking model virtual coupling random distribution longitudinal dynamics |
| title | Research on Multi-Mass Safety Braking Model for Heavy-Haul Trains Based on Random Distribution of Parameters |
| title_full | Research on Multi-Mass Safety Braking Model for Heavy-Haul Trains Based on Random Distribution of Parameters |
| title_fullStr | Research on Multi-Mass Safety Braking Model for Heavy-Haul Trains Based on Random Distribution of Parameters |
| title_full_unstemmed | Research on Multi-Mass Safety Braking Model for Heavy-Haul Trains Based on Random Distribution of Parameters |
| title_short | Research on Multi-Mass Safety Braking Model for Heavy-Haul Trains Based on Random Distribution of Parameters |
| title_sort | research on multi mass safety braking model for heavy haul trains based on random distribution of parameters |
| topic | heavy-haul train safety braking model virtual coupling random distribution longitudinal dynamics |
| url | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2024.04.006 |
| work_keys_str_mv | AT baijinlei researchonmultimasssafetybrakingmodelforheavyhaultrainsbasedonrandomdistributionofparameters AT wangyue researchonmultimasssafetybrakingmodelforheavyhaultrainsbasedonrandomdistributionofparameters AT jiangfan researchonmultimasssafetybrakingmodelforheavyhaultrainsbasedonrandomdistributionofparameters AT zhangzhengfang researchonmultimasssafetybrakingmodelforheavyhaultrainsbasedonrandomdistributionofparameters AT shike researchonmultimasssafetybrakingmodelforheavyhaultrainsbasedonrandomdistributionofparameters AT zhongpuhua researchonmultimasssafetybrakingmodelforheavyhaultrainsbasedonrandomdistributionofparameters |