3. Estimation of the Vertical Tire Forces

  1. Moustapha Doumiati,
  2. Ali Charara,
  3. Alessandro Victorino,
  4. Daniel Lechner and
  5. Bernard Dubuisson
  1. Moustapha Doumiati,
  2. Ali Charara,
  3. Alessandro Victorino,
  4. Daniel Lechner and
  5. Bernard Dubuisson

Published Online: 26 DEC 2012

DOI: 10.1002/9781118578988.ch3

Vehicle Dynamics Estimation using Kalman Filtering

Vehicle Dynamics Estimation using Kalman Filtering

How to Cite

Doumiati, M., Charara, A., Victorino, A., Lechner, D. and Dubuisson, B. (2012) Estimation of the Vertical Tire Forces, in Vehicle Dynamics Estimation using Kalman Filtering (eds M. Doumiati, A. Charara, A. Victorino, D. Lechner and B. Dubuisson), John Wiley & Sons, Inc., Hoboken, NJ USA. doi: 10.1002/9781118578988.ch3

Publication History

  1. Published Online: 26 DEC 2012
  2. Published Print: 17 DEC 2012

ISBN Information

Print ISBN: 9781848213661

Online ISBN: 9781118578988

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Keywords:

  • Kalman filter;
  • lateral transfer ratio (LTR);
  • vehicle’s mass;
  • vertical forces estimation;
  • vertical tire

Summary

This chapter outlines some of the fundamental concepts when dealing with roll dynamics. In addition, it proposes an original algorithm to estimate lateral transfer load and tire/road vertical forces, regardless of the tire model. Three observers are developed for this purpose based on the Kalman filter approach. Observer OdFz L is linear and is based on a roll dynamics model and provides lateral load transfer estimation. Observers OFz L and OFz E are derived from linear and nonlinear models. The lateral transfer ratio (LTR) rollover index parameter is also calculated and discussed within the context of estimating wheel vertical forces. The potential of the estimation process demonstrates that it may be possible to replace expensive dynamometric hub sensors by software observers. Although the identified mass tends toward the real mass value, a weak point of this approach is the determination of the vehicle’s mass.

Controlled Vocabulary Terms

Kalman filters; vehicle dynamics