• DocumentCode
    43795
  • Title

    Optimal Operation of Heavy-Haul Trains Equipped With Electronically Controlled Pneumatic Brake Systems Using Model Predictive Control Methodology

  • Author

    Lijun Zhang ; Xiangtao Zhuan

  • Author_Institution
    Sch. of Power & Mech. Eng., Wuhan Univ., Wuhan, China
  • Volume
    22
  • Issue
    1
  • fYear
    2014
  • fDate
    Jan. 2014
  • Firstpage
    13
  • Lastpage
    22
  • Abstract
    An optimal control methodology for heavy-haul trains with the objective to optimize the train´s operation in terms of energy consumption, velocity tracking, and operation safety is introduced. Rather than optimize the operation of the train at a specific position, this approach tries to schedule the train during a long period of travel in a model predictive control (MPC) framework; therefore, an effort is made so that the operation strategy of the train is optimal during a track section rather than at a specific position, as is done in existing literature. With this purpose, the cascade mass point model of the train is first simplified and transformed to facilitate the controller design. Then, an optimal controller is presented taking advantage of the MPC concept with the future behavior of the train and all operational constraints considered. Simulations demonstrate the feasibility as well as the advantages of the proposed approach.
  • Keywords
    brakes; control system synthesis; energy consumption; optimal control; pneumatic actuators; predictive control; rail traffic control; railway rolling stock; railway safety; MPC framework; cascade mass point model; controller design; electronically controlled pneumatic brake systems; energy consumption; heavy-haul trains operation; model predictive control methodology; operation safety; operational constraints; optimal control methodology; optimal controller; train scheduling; velocity tracking; Approximation methods; Couplers; Energy consumption; Force; Mathematical model; Optimization; Safety; Heavy-haul trains; model predictive control (MPC); operation optimization;
  • fLanguage
    English
  • Journal_Title
    Control Systems Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6536
  • Type

    jour

  • DOI
    10.1109/TCST.2013.2238235
  • Filename
    6450066