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2020 | OriginalPaper | Chapter

Sideslip Angle Estimation Using a Kinematics Based Unscented Kalman Filter and Digital Image Correlation

Authors: Wian Botes, Theunis R. Botha, P. Schalk Els

Published in: Advances in Dynamics of Vehicles on Roads and Tracks

Publisher: Springer International Publishing

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Abstract

Vehicle sideslip is an important input parameter that can be used to improve vehicle stability control. The sideslip angle is seen as a measure of vehicle lateral stability. This paper presents an inexpensive sideslip angle measurement algorithm which incorporates direct measurements and a kinematics-based model for sideslip estimation. The estimation algorithm uses Digital Image Correlation (DIC), to directly measure sideslip with a real-time sparse optical flow algorithm, and an Unscented Kalman Filter (UKF) to remove drift from the kinematics-based estimator. The method smooths the direct measurements from the DIC and other sensors while being independent of vehicle geometry.
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Metadata
Title
Sideslip Angle Estimation Using a Kinematics Based Unscented Kalman Filter and Digital Image Correlation
Authors
Wian Botes
Theunis R. Botha
P. Schalk Els
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-030-38077-9_186

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