Vehicle vibration velocity estimation based on Kalman filter

Fan Lu, Si Zhong Chen, Chang Liu, Man Hong Li, Yu Zhuang Zhao*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Based on the vehicle suspension system model, a Kalman filter was designed to estimate the vibration velocity by measuring the sprung mass accelerations and unsprung mass accelerations. The influence of the covariance matrix of process noise on vibration velocity estimation was analyzed. Then an adaptive Kalman filter based on predictive filter was discussed. The simulation results show that the designed Kalman filter can accurately estimate the vehicle vibration velocity in real time. The inaccuracy of process noise covariance matrix has larger influence on body velocity estimation, or even makes the filter fail. The adaptive Kalman filter can compensate the estimation error caused by the unknown process noise covariance and obtain accurate vehicle vibration velocity.

Original languageEnglish
Pages (from-to)111-116
Number of pages6
JournalZhendong yu Chongji/Journal of Vibration and Shock
Volume33
Issue number13
DOIs
Publication statusPublished - 15 Jul 2014

Keywords

  • Estimation
  • Kalman filter
  • Suspension
  • Vibration velocity

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