Abstract
Accurate and reliable estimation information of sideslip angle is very important for intelligent motion control and active safety control of an autonomous vehicle. To solve the problem of sideslip angle estimation of an autonomous vehicle, a sideslip angle fusion estimation method based on robust cubature Kalman filter and wheel-speed coupling relationship is proposed in this paper. The vehicle dynamics model, tire model, and wheel speed coupling model are established and discretized, and a robust cubature Kalman filter is designed for vehicle running state estimation according to the discrete vehicle model. An adaptive measurement-update solution of the robust cubature Kalman filter is presented to improve the robustness of estimation, and then, the wheel-speed coupling relationship is introduced to the measurement update equation of the robust cubature Kalman filter and an adaptive sideslip angle fusion estimation method is designed. The simulations in the CarSim-Simulink co-simulation platform and the actual vehicle road test are carried out, and the effectiveness of the proposed estimation method is validated by corresponding comparative analysis results.
Highlights
With the development of the automobile industry, people have higher and higher requirements for active safety and ride comfort of automobiles [1,2,3], and many advanced electronic control systems, such as electronic stabilization system, anti-lock braking system, traction control system, and anti-skid drive system, have been widely used in vehicles [4,5]
Zhang et al [26] established a nonlinear vehicle dynamic model with the time-varying characteristics of vehicle parameters being considered, and designed a novel vehicle sideslip angle estimation method using the finite-frequency H∞ approach to improve the robustness of estimation results
The simulation and experimental verification are carried out and the results show that the proposed fusion method has high estimation accuracy
Summary
With the development of the automobile industry, people have higher and higher requirements for active safety and ride comfort of automobiles [1,2,3], and many advanced electronic control systems, such as electronic stabilization system, anti-lock braking system, traction control system, and anti-skid drive system, have been widely used in vehicles [4,5]. Zhang et al [26] established a nonlinear vehicle dynamic model with the time-varying characteristics of vehicle parameters being considered, and designed a novel vehicle sideslip angle estimation method using the finite-frequency H∞ approach to improve the robustness of estimation results. Nam et al [41] developed a novel sideslip angle and roll angle estimation method with lateral tire force being obtained by vehicular sensors directly, in which the recursive least squares and Kalman filter is applied to track the vehicle running states. A sideslip angle fusion estimation method of an autonomous vehicle is proposed based on robust cubature Kalman filter (RCKF) and wheel-speed coupling relationship. A sideslip angle fusion estimation method is designed by reconstructing the measurement update equation using the wheel-speed coupling relationship, as to improve the accuracy and reliability of estimation results by using redundancy of measurement information.
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