On co-estimation and validation of vehicle driving states by a UKF-based approach
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Published:2021-01-18
Issue:1
Volume:12
Page:19-30
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ISSN:2191-916X
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Container-title:Mechanical Sciences
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language:en
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Short-container-title:Mech. Sci.
Author:
Wang Peng,Pang Hui,Xu Zijun,Jin Jiamin
Abstract
Abstract. It is necessary to acquire the accurate information of vehicle driving states for the implementation of automobile active safety control. To this end, this paper proposes an effective co-estimation method
based on an unscented Kalman filter (UKF) algorithm to accurately predict the sideslip angle, yaw rate, and longitudinal speed of a ground vehicle. First, a 3 degrees-of-freedom (DOFs) nonlinear vehicle dynamics model is
established as the nominal control plant. Then, based on CarSim software,
the simulation results of the front steer angle and longitudinal and lateral acceleration are obtained under a variety of working conditions, which are
regarded as the pseudo-measured values. Finally, the joint simulation of
vehicle state estimation is realized in the MATLAB/Simulink environment by using the pseudo-measured values and UKF algorithm concurrently. The results show
that the proposed UKF-based vehicle driving state estimation method is
effective and more accurate in different working scenarios compared with the
EKF-based estimation method.
Funder
National Natural Science Foundation of China
Publisher
Copernicus GmbH
Subject
Industrial and Manufacturing Engineering,Fluid Flow and Transfer Processes,Mechanical Engineering,Mechanics of Materials,Civil and Structural Engineering,Control and Systems Engineering
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