• DocumentCode
    2043480
  • Title

    Research on Rollover Early Warning Algorithm for Heavy Tractor- Semitrailer Based on PTR Metric

  • Author

    Zhu Tianjun ; Zong Changfu

  • Author_Institution
    Coll. of Mech. & Electron. Eng., Hebei Univ. of Eng., Handan
  • fYear
    2009
  • fDate
    23-24 May 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The paper sets up a vehicle dynamic model which is used to determine rollover risk of heavy tractor-semitrailer under various driving conditions; therefore it can help the driver to react accordingly. Using this real-time dynamic model, the predictive time to rollover (PTR), which is decided by load transfer ratio (LTR) of trailer axle when it reaches its limit value, can be determined as the rollover early warning index. The paper suggests a new algorithm of rollover early warning for heavy tractor-semitrailer based on accurate PTR metric which is obtained through EKF observer. The verification of the vehicle dynamic model is realized by Trucksim vehicle model and the simulation results show that the predicted values of the LTR are close to the simulated ones, and hence the proposed algorithm is potentially suitable for application in rollover risk assessment.
  • Keywords
    Kalman filters; agricultural machinery; observers; predictive control; road vehicles; vehicle dynamics; EKF observer; Trucksim vehicle model; driving condition; heavy tractor-semitrailer; load transfer ratio; predictive time to rollover metric; real-time dynamic model; rollover early warning algorithm; rollover early warning index; rollover risk assessment; trailer axle; vehicle dynamic model; Alarm systems; Automotive engineering; Axles; Potential energy; Power engineering and energy; Predictive models; Road accidents; State estimation; Vehicle dynamics; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-3893-8
  • Electronic_ISBN
    978-1-4244-3894-5
  • Type

    conf

  • DOI
    10.1109/IWISA.2009.5073081
  • Filename
    5073081