• DocumentCode
    3291452
  • Title

    Automotive transmission clutch fill optimal control: An experimental investigation

  • Author

    Xingyong Song ; Zulkefli, M.A.M. ; Zongxuan Sun

  • Author_Institution
    Mech. Eng. Dept., Univ. of Minnesota, Minneapolis, MN, USA
  • fYear
    2010
  • fDate
    June 30 2010-July 2 2010
  • Firstpage
    2748
  • Lastpage
    2753
  • Abstract
    Clutch to clutch shift control technology, which is the key enabler for a compact and low cost automotive transmission design, is important for both automatic and hybrid transmissions. To ensure a smooth clutch to clutch shift, precise synchronization between the on-coming and off-going clutches is critical. This further requires the on-coming clutch to be filled and ready for engagement at the predetermined time. To optimize this process, the clutch fill was formulated as an optimization problem in our previous work and a customized dynamic programming method was proposed as a solution. Following this idea, this paper presents the clutch fill experimental setup and the optimal control implementation. First, a clutch fill dynamic model, which captures the key dynamics in the clutch fill process, is constructed and analyzed. Second, the customized DP method is implemented to obtain the optimal pressure profile subjected to specified constraints. To validate the proposed method, a transmission clutch fixture has been designed and built in the laboratory. Finally, the experiment is conducted to track the optimal input pressure for clutch fill.
  • Keywords
    automotive components; clutches; dynamic programming; fixtures; optimal control; automotive transmission clutch fill optimal control; clutch to clutch shift control technology; dynamic programming method; optimization problem; transmission clutch fixture; Automotive engineering; Engines; Optimal control; Optimization methods; Pistons; Seals; Springs; Torque; Vehicle driving; Vehicle dynamics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2010
  • Conference_Location
    Baltimore, MD
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4244-7426-4
  • Type

    conf

  • DOI
    10.1109/ACC.2010.5531417
  • Filename
    5531417