• DocumentCode
    1798039
  • Title

    Cloud aided semi-active suspension control

  • Author

    Zhaojian Li ; Kolmanovsky, Ilya ; Atkins, Ella ; Jianbo Lu ; Filev, Dimitar ; Michelini, John

  • Author_Institution
    Dept. of Aerosp. Eng., Univ. of Michigan, Ann Arbor, MI, USA
  • fYear
    2014
  • fDate
    9-12 Dec. 2014
  • Firstpage
    76
  • Lastpage
    83
  • Abstract
    This paper considers the problem of vehicle suspension control from the perspective of a Vehicle-to-Cloud-to-Vehicle (V2C2V) distributed implementation. A simplified variant of the problem is examined based on the linear quarter-car model of semi-active suspension dynamics. Road disturbance is modeled as a combination of a known road profile, an unmeasured stochastic road profile and potholes. Suspension response when the vehicle hits the pothole is modeled as an impulsive change in wheel velocity with magnitude linked to physical characteristics of the pothole and of the vehicle. The problem of selecting the optimal damping mode from a finite set of damping modes is considered, based on road profile data. The information flow and V2C2V implementation are defined based on partitioning the computations and data between the vehicle and the cloud. A simulation example is presented.
  • Keywords
    cloud computing; mechanical engineering computing; road vehicles; suspensions (mechanical components); vehicle dynamics; V2C2V; cloud aided semiactive suspension control; linear quarter-car model; optimal damping mode; potholes; road disturbance; semiactive suspension dynamics; unmeasured stochastic road profile; vehicle suspension control; Damping; Roads; Stochastic processes; Suspensions; Tires; Vehicles; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Vehicles and Transportation Systems (CIVTS), 2014 IEEE Symposium on
  • Conference_Location
    Orlando, FL
  • Type

    conf

  • DOI
    10.1109/CIVTS.2014.7009481
  • Filename
    7009481