In the heavy-haul train application scenario, before the locomotive performs the traction task, it is necessary to group multiple locomotives to obtain sufficient power. In the traditional locomotive marshalling, each locomotive needs to be equipped with crew members to coordinate with each other to complete the marshalling operation. The efficiency is low and there is the risk of misoperation. In order to further realizing the goal of intelligent driving of heavy-haul train to improve the operation efficiency, increase safety, and reduce manual operations, this paper proposes an automatic marshalling method for intelligent driving heavy-haul trains. In the automatic marshalling operation, the ground Automatic Train Control System (ATS) is responsible for the issuance of marshalling parameter command and process control, which is transmitted to the on-board equipment through wireless network. The marshalling data processing and feedback information transfer are carried out by the on-board control device host (Automatic Train Operation, ATO) of intelligent driving system, and the marshalling execution and feedback equipment use the Synchronous operation Control Equipment (OCE) of the wireless coupling control system, Through the above methods, The automatic marshalling of intelligent driving heavy-haul locomotive can be realized, and the efficiency and reliability of marshalling operations are improved.


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    Titel :

    Design and Implementation of Automatic Marshalling for Intelligent Driving Locomotive of Heavy-Haul Train


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Qin, Yong (Herausgeber:in) / Jia, Limin (Herausgeber:in) / Liang, Jianying (Herausgeber:in) / Liu, Zhigang (Herausgeber:in) / Diao, Lijun (Herausgeber:in) / An, Min (Herausgeber:in) / Li, Tiebing (Autor:in) / Xiong, Chaokun (Autor:in) / Jiang, Fan (Autor:in) / Zhu, Long (Autor:in)

    Kongress:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2021 October 21, 2021 - October 23, 2021



    Erscheinungsdatum :

    23.02.2022


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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