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 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.

Automated summary

In this article, a real-time vehicle sideslip angle state observer based on the EKF algorithm is proposed. The observer model is established by combining the EKF and least squares methods, with a self-adapted truncation procedure. The calculation of the Jacobi matrix is transformed into the frequency domain, and a self-adapted update noise estimation method and an initial value setting strategy are proposed. Hardware-in-the-loop simulation is carried out to verify and analyze the real-time reliability of the estimation method using RMSE.