• DocumentCode
    2445563
  • Title

    Identification of cornering stiffness during lane change maneuvers

  • Author

    Arndt, M. ; Ding, E.L. ; Massel, T.

  • Author_Institution
    Dept. of Phys. Eng., Gelsenkirchen Univ. of Appl. Sci., Germany
  • Volume
    1
  • fYear
    2004
  • fDate
    2-4 Sept. 2004
  • Firstpage
    344
  • Abstract
    The aim of designing an integrated sensor monitoring platform is to monitor all existing sensors and to estimate the vehicle state variables centrally in order to provide the other function components with information about the actual system state and the vehicle dynamics. One essential part of that platform is to describe the vehicle dynamics as precisely as possible with the help of mathematical models. The cornering stiffness of tires plays an important role in the description of the lateral dynamics. The goal of this contribution is to develop a method for identifying the cornering stiffness coefficients. The identified coefficients are inserted into the corresponding models. Then, investigations of the identification method and the adapted models are carried out in a virtual vehicle. Finally, test results using this virtual vehicle are demonstrated and discussed.
  • Keywords
    least squares approximations; mechanical variables control; parameter estimation; road vehicles; state estimation; tyres; vehicle dynamics; cornering stiffness coefficient estimation; identification method; integrated sensor monitoring platform; lane change maneuvers; least squares methods; mathematical models; tire stiffness; vehicle dynamics; vehicle state variables estimation; virtual vehicle; Force sensors; Mathematical model; Monitoring; Roads; Sensor systems; State estimation; Tires; Transfer functions; Vehicle dynamics; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Applications, 2004. Proceedings of the 2004 IEEE International Conference on
  • Print_ISBN
    0-7803-8633-7
  • Type

    conf

  • DOI
    10.1109/CCA.2004.1387235
  • Filename
    1387235