Cascaded Observers to Improve Lateral Vehicle State and Tyre Parameter Estimates


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.