Research on the pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimization
The pneumatic-electric braking operation of heavy-haul trains on long and steep downgrade sections is fundamentally an optimal control problem, involving nonlinear state constraints, control constraints, and long-distance end constraints. Traditional collaborative control strategies for pneumatic-el...
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| Format: | Article |
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Editorial Department of Electric Drive for Locomotives
2025-01-01
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| Series: | 机车电传动 |
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| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2025.01.014 |
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| author | ZHANG Zhengfang SHI Ke LIU Haitao WANG Yue FENG Ling |
| author_facet | ZHANG Zhengfang SHI Ke LIU Haitao WANG Yue FENG Ling |
| author_sort | ZHANG Zhengfang |
| collection | DOAJ |
| description | The pneumatic-electric braking operation of heavy-haul trains on long and steep downgrade sections is fundamentally an optimal control problem, involving nonlinear state constraints, control constraints, and long-distance end constraints. Traditional collaborative control strategies for pneumatic-electric braking often struggle to simultaneously address these constraints, making it difficult to ensure the safety and stability of heavy-haul trains during the pneumatic-electric braking coordinative control process. To tackle this issue, this paper proposes a pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimization. Firstly, the dynamic characteristics of heavy-haul trains were analyzed, leading to the extraction of nonlinear state constraints, control constraints, and end constraints in the pneumatic-electric braking coordinative control process. Next, a gradient search was performed focusing on the stability objective within the nonlinear state constraints and control constraints, which resulted in the formation of a finite set sequence based on the position domain. At the same time, a neural network was designed to identify parameters for a nonlinear pneumatic braking model, thereby yielding predicted pneumatic braking forces. Subsequently, an A * algorithm was developed for iterative refinement within the finite set sequence, collaborative control sequence that satisfies the end constraints. Finally, the effectiveness of the proposed pneumatic-electric collaborative control strategy for heavy-haul trains was verified through a semi-physical simulation platform. |
| format | Article |
| id | doaj-art-723efe57fd0347ed9f2a2dfb17768dbf |
| institution | DOAJ |
| issn | 1000-128X |
| language | zho |
| publishDate | 2025-01-01 |
| publisher | Editorial Department of Electric Drive for Locomotives |
| record_format | Article |
| series | 机车电传动 |
| spelling | doaj-art-723efe57fd0347ed9f2a2dfb17768dbf2025-08-20T03:09:32ZzhoEditorial Department of Electric Drive for Locomotives机车电传动1000-128X2025-01-0111412189786910Research on the pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimizationZHANG ZhengfangSHI KeLIU HaitaoWANG YueFENG LingThe pneumatic-electric braking operation of heavy-haul trains on long and steep downgrade sections is fundamentally an optimal control problem, involving nonlinear state constraints, control constraints, and long-distance end constraints. Traditional collaborative control strategies for pneumatic-electric braking often struggle to simultaneously address these constraints, making it difficult to ensure the safety and stability of heavy-haul trains during the pneumatic-electric braking coordinative control process. To tackle this issue, this paper proposes a pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimization. Firstly, the dynamic characteristics of heavy-haul trains were analyzed, leading to the extraction of nonlinear state constraints, control constraints, and end constraints in the pneumatic-electric braking coordinative control process. Next, a gradient search was performed focusing on the stability objective within the nonlinear state constraints and control constraints, which resulted in the formation of a finite set sequence based on the position domain. At the same time, a neural network was designed to identify parameters for a nonlinear pneumatic braking model, thereby yielding predicted pneumatic braking forces. Subsequently, an A * algorithm was developed for iterative refinement within the finite set sequence, collaborative control sequence that satisfies the end constraints. Finally, the effectiveness of the proposed pneumatic-electric collaborative control strategy for heavy-haul trains was verified through a semi-physical simulation platform.http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2025.01.014heavy-haul trainlong and steep downgrade sectionlongitudinal dynamicspneumatic-electric braking coordinativecontrolnonlinear finite setheuristic dual-end optimizationheavy-haul railway |
| spellingShingle | ZHANG Zhengfang SHI Ke LIU Haitao WANG Yue FENG Ling Research on the pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimization 机车电传动 heavy-haul train long and steep downgrade section longitudinal dynamics pneumatic-electric braking coordinativecontrol nonlinear finite set heuristic dual-end optimization heavy-haul railway |
| title | Research on the pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimization |
| title_full | Research on the pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimization |
| title_fullStr | Research on the pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimization |
| title_full_unstemmed | Research on the pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimization |
| title_short | Research on the pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimization |
| title_sort | research on the pneumatic electric braking collaborative control strategy for heavy haul trains based on heuristic dual end optimization |
| topic | heavy-haul train long and steep downgrade section longitudinal dynamics pneumatic-electric braking coordinativecontrol nonlinear finite set heuristic dual-end optimization heavy-haul railway |
| url | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2025.01.014 |
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