Velocity and normal tyre force estimation for heavy trucks based on vehicle dynamic simulation considering the road slope angle

Zeyu Ma, Yunqing Zhang, James Yang

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

A precise estimation of vehicle velocities can be valuable for improving the performance of the vehicle dynamics control (VDC) system and this estimation relies heavily upon the accuracy of longitudinal and lateral tyre force calculation governed by the prediction of normal tyre forces. This paper presents a computational method based on the unscented Kalman filter (UKF) method to estimate both longitudinal and lateral velocities and develops a novel quasi-stationary method to predict normal tyre forces of heavy trucks on a sloping road. The vehicle dynamic model is constructed with a planar dynamic model combined with the Pacejka tyre model. The novel quasi-stationary method for predicting normal tyre forces is able to characterise the typical chassis configuration of the heavy trucks. The validation is conducted through comparing the predicted results with those simulated by the TruckSim and it has a good agreement between these results without compromising the convergence speed and stability.

Original languageEnglish
Pages (from-to)163-193
Number of pages31
JournalVehicle System Dynamics
Volume54
Issue number2
DOIs
StatePublished - Feb 1 2016

Keywords

  • Unscented Kalman filter
  • normal tyre forces
  • state estimation
  • vehicle system dynamics

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