• DocumentCode
    3526374
  • Title

    A Neural Network pressure control approach for automotive Variable Bleed Solenoid

  • Author

    Pando, Luis ; Garza, Luis E.

  • Author_Institution
    Delphi Automotive Syst., Juarez, Mexico
  • fYear
    2010
  • fDate
    23-25 June 2010
  • Firstpage
    1491
  • Lastpage
    1496
  • Abstract
    In this paper we describe a novel pressure control approach applied to a Variable Bleed Solenoid (VBS) that resides inside a vehicle automatic transmission for clutch engaging purposes. The pressure control approach is based on a Neural Network Scheme that has been previously trained to learn from the inputs and outputs the nonlinear dynamics experimented on an automatic transmission working on the field. The Neural Network control technique shows a better performance, when compared against a classical method based on a look up pressure table, because avoids VBS output pressure instability especially when the system is subjected to oil temperature fluctuation, input pressure instability, current fluctuation and thermal degradation.
  • Keywords
    Artificial neural networks; Input variables; Neurons; Petroleum; Pressure control; Solenoids; Vehicles; automatic transmission; inverse control; neural networks; variable bleed solenoid;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control & Automation (MED), 2010 18th Mediterranean Conference on
  • Conference_Location
    Marrakech, Morocco
  • Print_ISBN
    978-1-4244-8091-3
  • Type

    conf

  • DOI
    10.1109/MED.2010.5547837
  • Filename
    5547837