Vehicular Vertical Tire Forces Estimation Using Unscented Kalman Filter

被引:0
|
作者
Kim, Suk Won [1 ]
Jeong, Yong Woo [1 ]
Kim, Jin Sung [1 ]
Lee, Seung-Hi [1 ]
Chung, Chung Choo [2 ]
机构
[1] Hanyang Univ, Dept Elect Engn, Seoul 04763, South Korea
[2] Hanyang Univ, Div Elect & Biomed Engn, Seoul 04763, South Korea
关键词
VEHICLE STATE ESTIMATION; ROLL;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose a vertical forces estimator based on Unscented Kalman Filter (UKF). The vehicle dynamics is so complicated that it is common to estimate its motion using its reduced model based on a decoupled model consisting of a lateral dynamic model and a longitudinal dynamic model on an even road. The decoupled model is not effective in estimating vehicle motion, when the vehicle is severely maneuvered causing high rolling motion. In this paper, we propose a new estimator to estimate the roll angle and lateral acceleration in using UKF algorithm for 3-Degree-Of-Freedom Model. Then a lateral load transfer model and a longitudinal load transfer model are used to estimate the vertical load force on each tire. From the numerical simulation study using MATLAB/CarSim, we observed that there were good agreements between ground truth and the estimated vertical tire forces even the vehicle was driven at 60 km/hour speed by a sine wave steering wheel angle with +/- 60 degrees at 0.1Hz on various driving roads.
引用
收藏
页码:325 / 330
页数:6
相关论文
共 50 条
  • [1] Identification of tire forces using Dual Unscented Kalman Filter algorithm
    Davoodabadi, Iraj
    Ramezani, Ali Asghar
    Mahmoodi-k, Mehdi
    Ahmadizadeh, Pouyan
    NONLINEAR DYNAMICS, 2014, 78 (03) : 1907 - 1919
  • [2] Identification of tire forces using Dual Unscented Kalman Filter algorithm
    Iraj Davoodabadi
    Ali Asghar Ramezani
    Mehdi Mahmoodi-k
    Pouyan Ahmadizadeh
    Nonlinear Dynamics, 2014, 78 : 1907 - 1919
  • [3] Erratum to: Identification of tire forces using Dual Unscented Kalman Filter algorithm
    Iraj Davoodabadi
    Asghar Ramezani
    Mehdi Mahmoodi-k
    Pouyan Ahmadizadeh
    Nonlinear Dynamics, 2014, 78 : 2985 - 2985
  • [4] Tire Force Estimation for a Passenger Vehicle with the Unscented Kalman Filter
    Hamann, Harry
    Hedrick, J. Karl
    Rhode, Stephan
    Gauterin, Frank
    2014 IEEE INTELLIGENT VEHICLES SYMPOSIUM PROCEEDINGS, 2014, : 814 - 819
  • [5] Unscented Kalman filter for real-time vehicle lateral tire forces and sideslip angle estimation
    Doumiati, Moustapha
    Victorino, Alessandro
    Charara, Ali
    Lechner, Daniel
    2009 IEEE INTELLIGENT VEHICLES SYMPOSIUM, VOLS 1 AND 2, 2009, : 901 - 906
  • [6] Combined Estimation of Vehicle Slip Angle and Lateral Tire Forces with an Unscented Kalman Filter with Outlier Detection
    Speth, Peter
    Buchholz, Michael
    2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), 2019, : 2963 - 2968
  • [7] POSITION ESTIMATION USING UNSCENTED KALMAN FILTER
    Konatowski, Stanislaw
    INTERNATIONAL JOURNAL OF ELECTRONICS AND TELECOMMUNICATIONS, 2006, 52 (02) : 229 - 243
  • [8] Identification of tire forces using Dual Unscented Kalman Filter algorithm (vol 78, pg 1907, 2014)
    Davoodabadi, Iraj
    Ramezani, Asghar
    Mahmoodi-k, Mehdi
    Ahmadizadeh, Pouyan
    NONLINEAR DYNAMICS, 2014, 78 (04) : 2985 - 2985
  • [9] Wheelset states estimation using unscented Kalman filter
    Yang, Z.
    Lu, Z. G.
    Wang, X. C.
    Huang, Q.
    DYNAMICS OF VEHICLES ON ROADS AND TRACKS, VOL 2, 2018, : 1071 - 1076
  • [10] Battery State Estimation Using Unscented Kalman Filter
    Zhang, Fei
    Liu, Guangjun
    Fang, Lijin
    ICRA: 2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-7, 2009, : 3574 - +