Abstract
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.
Original language | English |
---|---|
Publication status | Accepted/In press - 2024 |
Event | SAE 28th Small Powertrains and Energy Systems Technology Conference, SETC 2024 - Bangkok, Thailand Duration: 4 Nov 2024 → 7 Nov 2024 |
Conference
Conference | SAE 28th Small Powertrains and Energy Systems Technology Conference, SETC 2024 |
---|---|
Country/Territory | Thailand |
City | Bangkok |
Period | 04.11.2024 → 07.11.2024 |
Keywords
- motorcycle dynamics
- tire lateral forces
- robust state estimation
Fingerprint
Dive into the research topics of 'A Two-Step Approach for Tire Lateral Force Observation for Motorcycles'. Together they form a unique fingerprint.Prizes
-
High Quality Paper Award
Winkler, A. (Recipient), Grabmair, G. (Recipient) & Reger, J. (Recipient), 2024
Prize