Estimation of Vehicle Sideslip Angle Based-on Unscented Kalman Filter

The sideslip angle of the center of mass is one of the important control variables in the steering stability control system of forklift, and it is also difficult to measure directly. According to the characteristics of the sideslip angle which is not easy to measure, the paper takes the four wheel steering forklift of the front wheel and rear wheel active control as the research object. Based on the nonlinear two degree of freedom (2DOF) forklift dynamics model and the driver-forklift closed-loop system model, and based on extended Kalman filter (EKF) and unscented Kalman filter (UKF), the sideslip angle estimation model is established, and the steps of UKF algorithm are given in detail. Simulation results show that the estimation accuracy of UKF algorithm is better than that of EKF algorithm in either open-loop or closed-loop systems, it can better meet the state estimation requirements of forklift.