Research on a Real-Time Estimation Method of Vehicle Sideslip Angle Based on EKF

In this article, a real-time vehicle sideslip angle state observer is proposed, which is based on the EKF algorithm. Firstly, based on a 2-DOF dynamical model and the tire lateral force model, the vehicle sideslip angle state observer model with a self-adapted truncation procedure is established by...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-04, Vol.22 (9), p.3386
Main Authors: Sun, Wen, Wang, Zhenyuan, Wang, Junnian, Wang, Xiangyu, Liu, Lili
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Analysis
Dynamic models
dynamical model
extended Kalman filter (EKF)
Fuzzy logic
Geometry
Hardware-in-the-loop simulation
Kinematics
least squares method
Methods
Neural networks
Noise
Optimization algorithms
Real time
Reliability analysis
root mean square error (RMSE)
Sensors
Sideslip
State observers
Tires
Traffic accidents & safety
vehicle sideslip angle
Vehicles
Velocity
Working conditions
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Summary:In this article, a real-time vehicle sideslip angle state observer is proposed, which is based on the EKF algorithm. Firstly, based on a 2-DOF dynamical model and the tire lateral force model, the vehicle sideslip angle state observer model with a self-adapted truncation procedure is established by combining the EKF and the least squares methods. The calculation of the Jacobi matrix in the time domain is transformed into a calculation in the frequency domain. A self-adapted update noise estimation method and an initial value setting strategy are proposed as well. Finally, a hardware-in-the-loop simulation is carried out by Matlab/Simulink-CarSim-dSPACE, and the real-time reliability of the estimation method is verified and analyzed by RMSE.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22093386