Vehicle sideslip estimator using load sensing bearings

Journal Article (2016)
Author(s)

A Kunnappillil Madhusudhanan (TNO, TU Delft - Dynamics of Micro and Nano Systems)

M Corno (Politecnico di Milano)

Edward Holweg (TU Delft - OLD Intelligent Vehicles & Cognitive Robotics, SKF)

Research Group
OLD Intelligent Vehicles & Cognitive Robotics
DOI related publication
https://doi.org/10.1016/j.conengprac.2016.05.008
More Info
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Publication Year
2016
Language
English
Research Group
OLD Intelligent Vehicles & Cognitive Robotics
Volume number
54
Pages (from-to)
46-57

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°.

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