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  • 标题:Vehicle State Information Estimation with the Unscented Kalman Filter:
  • 本地全文:下载
  • 作者:Hongbin Ren ; Sizhong Chen ; Gang Liu
  • 期刊名称:Advances in Mechanical Engineering
  • 印刷版ISSN:1687-8140
  • 电子版ISSN:1687-8140
  • 出版年度:2014
  • 卷号:6
  • 页码:1-11
  • DOI:10.1155/2014/589397
  • 语种:English
  • 出版社:Sage Publications Ltd.
  • 摘要:The vehicle state information plays an important role in the vehicle active safety systems; this paper proposed a new concept to estimate the instantaneous vehicle speed, yaw rate, tire forces, and tire kinemics information in real time. The estimator is based on the 3DoF vehicle model combined with the piecewise linear tire model. The estimator is realized using the unscented Kalman filter (UKF), since it is based on the unscented transfer technique and considers high order terms during the measurement and update stage. The numerical simulations are carried out to further investigate the performance of the estimator under high friction and low friction road conditions in the MATLAB/Simulink combined with the Carsim environment. The simulation results are compared with the numerical results from Carsim software, which indicate that UKF can estimate the vehicle state information accurately and in real time; the proposed estimation will provide the necessary and reliable state information to the vehicle controller in the future.
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