Numerical Achieved Extended Kalman Filter State Observer Design Based on a Vehicle Model Containing UniTire Model

Zhao Pan, Changfu Zong, Dan Hu, Hongyu Zheng, Kan Wu

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

It is difficult to obtain state variables accurately or economically while vehicle is moving, however these state variables are significant for chassis control. Although many researches have been done, a complex model always leads to a control system with poor real-time performance, while simple model cannot show the real characteristics. So, in order to estimate the value of yaw rate and side slip angle accurately and sententiously, an Extended Kalman Filter (EKF) observer is proposed, which is based on an ameliorated 2-DOF “bicycle model”. The EKF algorithm is achieved numerically and verified by the results from the real field test.
Original languageEnglish
JournalSAE Technical Papers
DOIs
Publication statusPublished - 23 Jun 2008

Fingerprint Dive into the research topics of 'Numerical Achieved Extended Kalman Filter State Observer Design Based on a Vehicle Model Containing UniTire Model'. Together they form a unique fingerprint.

  • Cite this