State estimation and verification of five-axle heavy-duty special vehicle based on EKF

Abstract

Multi-axle heavy-duty special vehicles have the characteristics of large load and highe center of mass, which result the possibility of steering instability under high maneuvering conditions. The sideslip angle and yaw rate are the key criteria for measuring vehicle handling stability. If it is measured directly by on-board sensors, there are problems such as difficult measurement, high cost and long-term error. Therefore, the research on the state estimation of five-axle heavyduty vehicles is carried out. Firstly, based on the nonlinear three-degree-of-freedom vehicle model, a multi-axis heavyduty vehicle state observer based on Extended Kalman Filter is established to predict and estimate the yaw rate, sideslip angle and longitudinal speed of the vehicle. Then, a 13-degree-of-freedom dynamic model of a five-axle special vehicle is built based on Matlab/Simulink, and the driving state monitoring system is used to conduct real vehicle experiments to verify the accuracy of the model, which provides a theoretical basis for estimating the model and a verification simulation platform. Finally, the 13-degree-of-freedom model is used as the simulation platform to verify the fishhook condition, the double-line moving condition and the sinusoidal input condition. The research results show that the state estimator based on the nonlinear three-degree-of-freedom vehicle model can realize the dynamic estimation of the parameters of longitudinal velocity, yaw rate and sideslip angle.