Vehicle sideslip estimator using load sensing bearings

Anil Kunnappillil Madhusudhanan, Matteo Corno, Edward Holweg

Research output: Contribution to journalArticleScientificpeer-review

19 Citations (Scopus)

Abstract

This paper investigates the potential of load based vehicle sideslip estimation. Different techniques to measure tyre forces have been presented over the years; so far no technique has made it to the market. This paper considers a new technology based on load sensing bearings, which provides tyre force measurements. Based on the features of the sensor, a vehicle sideslip angle estimator is designed, analyzed and tested. The paper shows that direct tyre force sensing has mainly two advantages over traditional model-based estimators: primarily, it avoids the use of tyre models, which are heavily affected by uncertainties and modeling errors and secondarily, providing measurements on the road plane, it is less prone to errors introduced by roll and pitch dynamics. Extensive simulation tests along with a detailed analysis of experimental tests performed on an instrumented vehicle prove that the load based estimation outperforms the kinematic model-based benchmark yielding a root mean square error of 0.15°.

Original languageEnglish
Pages (from-to)46-57
JournalControl Engineering Practice
Volume54
DOIs
Publication statusPublished - 2016

Keywords

  • Kalman filter
  • Load sensing bearing
  • Observability
  • State estimation
  • Vehicle sideslip

Fingerprint Dive into the research topics of 'Vehicle sideslip estimator using load sensing bearings'. Together they form a unique fingerprint.

Cite this