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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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previous chapter Vehicle Sideslip Estimation for Four-Wheel-Steering Vehicles Using a Particle Filter
next chapter An Investigation on the Effect of Lateral Motion on Normal Forces Acting on Each Tires for Nonholonomic Electric Vehicle: Experimental Results Validation
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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
Book
Advances in Dynamics of Vehicles on Roads and Tracks

Print ISBN: 978-3-030-38076-2

Electronic ISBN: 978-3-030-38077-9

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-38077-9_186

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