A Two-Step Approach for Tire Lateral Force Observation for Motorcycles

<div class="section abstract"><div class="htmlview paragraph">This study presents a two-step method for estimating motorcycle tire lateral forces, which are critical to the safety of driver assistance systems. In the pre-filtering stage, a partial attitude of the motorcycle is estimated using a Kalman filter and a kinematic model. In the observation stage, the side slip angle and subsequently the tire lateral forces are provided by a sliding mode observer. It extends previous research by incorporating both out-of-plane and in-plane dynamics. The paper also proposes an approach for selecting the Kalman filter parameters. An approach to identify the stochastic sensor errors of the inertial measurement unit is presented. The identified parameters are used as a basis for the selection of the covariances. The overall study provides a practical implementation strategy and demonstrates its applicability in real-world scenarios. The experiments show the results of the lateral force estimation and its relation to the friction ellipse. The effectiveness of the proposed observer concept is evaluated using simulation data and measured data.</div></div>

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Publication Details

Journal
SAE International Journal of Advances and Current Practices in Mobility
Published
2025-04-17
DOI
https://doi.org/10.4271/2024-32-0043
Primary Topic
Vehicle Dynamics and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

A Two-Step Approach for Tire Lateral Force Observation for Motorcycles

Alexander Winkler, Johann Reger, Gernot Grabmair
SAE International Journal of Advances and Current Practices in Mobility
Vehicle Dynamics and Control Systems
article

A Two-Step Approach for Tire Lateral Force Observation for Motorcycles

Alexander Winkler, Johann Reger, Gernot Grabmair
article en

Abstract

<div class="section abstract"><div class="htmlview paragraph">This study presents a two-step method for estimating motorcycle tire lateral forces, which are critical to the safety of driver assistance systems. In the pre-filtering stage, a partial attitude of the motorcycle is estimated using a Kalman filter and a kinematic model. In the observation stage, the side slip angle and subsequently the tire lateral forces are provided by a sliding mode observer. It extends previous research by incorporating both out-of-plane and in-plane dynamics. The paper also proposes an approach for selecting the Kalman filter parameters. An approach to identify the stochastic sensor errors of the inertial measurement unit is presented. The identified parameters are used as a basis for the selection of the covariances. The overall study provides a practical implementation strategy and demonstrates its applicability in real-world scenarios. The experiments show the results of the lateral force estimation and its relation to the friction ellipse. The effectiveness of the proposed observer concept is evaluated using simulation data and measured data.</div></div>

SAE International Journal of Advances and Current Practices in MobilityVol. 07(4)
Technische Universität Ilmenau (DE), University of Applied Sciences Upper Austria (AT)
Openalex Percentile: Top 93%
Vehicle Dynamics and Control Systems
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