• DocumentCode
    2684282
  • Title

    Vehicle velocity estimation based on Adaptive Kalman Filter

  • Author

    Chu, Liang ; Shi, Yanru ; Zhang, Yongsheng ; Ou, Yang ; Xu, Mingfa

  • Author_Institution
    Key Lab. of Automobile Dynamic Simulation, Jilin Univ., Changchun, China
  • Volume
    3
  • fYear
    2010
  • fDate
    24-26 Aug. 2010
  • Firstpage
    492
  • Lastpage
    495
  • Abstract
    Due to use sensors to measure vy and vx are very expensive, it is necessary to estimate vy and vx from other variables measured easily. A novel method based on Adaptive Kalman Filter (AKF) is proposed for estimation of vy and vx in this paper by updating the mean and covariance of noise online. The estimation values are compared with simulator values from CarSim. The results demonstrate that the proposed method is robust and can improve the estimation accuracy of vy and vx.
  • Keywords
    adaptive Kalman filters; covariance analysis; road vehicles; robust control; velocity control; CarSim; adaptive Kalman filter; noise covariance; robust method; vehicle velocity estimation; Estimation; Tires; HSRI tire model; adaptive Kalma filter; lateral velocity; longitudinal velocity; vehicle dynamic model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4244-7957-3
  • Type

    conf

  • DOI
    10.1109/CMCE.2010.5610261
  • Filename
    5610261
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2684282