Title: Cascaded observers to improve lateral vehicle state and tyre parameter estimates

Authors: Robert Daily, William Travis, David M. Bevly

Addresses: Department of Mechanical Engineering, GPS and Vehicle Dynamics Lab, Auburn University, AL 36849, USA. ' Department of Mechanical Engineering, GPS and Vehicle Dynamics Lab, Auburn University, AL 36849, USA. ' Department of Mechanical Engineering, GPS and Vehicle Dynamics Lab, Auburn University, AL 36849, USA

Abstract: This paper proposes a method to produce high update, accurate, observable estimates of vehicle sideslip, utilising a two antenna GPS system. Measurements are blended with a kinematic Kalman filter to get high update sideslip estimates, which are used to predict the Dugoff tyre parameters. The parameters are then used in a model-based Kalman filter, which can provide more accurate vehicle state estimates even in the event of a GPS outage. Tyre force estimation is tested with experimental data on high and low friction surfaces, and validated by the performance of the model-based Kalman filter using the identified tyre parameters.

Keywords: vehicle dynamics; sideslip; dual antenna GPS; Kalman filter; tyre force estimation; kinematic modelling; cascaded observers; lateral vehicle state; tyre parameter estimates; global positioning systems; vehicle state estimation.

DOI: 10.1504/IJVAS.2007.016403

International Journal of Vehicle Autonomous Systems, 2007 Vol.5 No.3/4, pp.230 - 255

Available online: 28 Dec 2007 *

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