An Adaptive Unscented Kalman Filter for the Estimation of the Vehicle Velocity Components, Slip Angles, and Slip Ratios in Extreme Driving Manoeuvres

An Adaptive Unscented Kalman Filter for the Estimation of the Vehicle Velocity Components, Slip Angles, and Slip Ratios in Extreme Driving Manoeuvres

This paper presents a novel unscented Kalman filter (UKF) implementation with adaptive covariance matrices (ACMs), to accurately estimate the longitudinal and lateral components of vehicle velocity, and thus the sideslip angle, tire slip angles, and tire slip ratios, also in extreme driving conditio...

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Bibliographic Details
Main Authors: Aymen Alshawi, Stefano De Pinto, Pietro Stano, Sebastiaan van Aalst, Kylian Praet, Emilie Boulay, Davide Ivone, Patrick Gruber, Aldo Sorniotti
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Sensors
Subjects:
unscented Kalman filter
sideslip angle estimation
vehicle speed estimation
slip ratio estimation
state estimation
covariance matrix adaptation
Online Access:https://www.mdpi.com/1424-8220/24/2/436

Internet

https://www.mdpi.com/1424-8220/24/2/436

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