State Estimation of the Electric Drive Articulated Dump Truck Based on UKF

The requirements of vehicle dynamic stability control are higher than ever as the significant increase of electric drive articulated vehicle speed. According to the construction features of articulated dumping truck and nonlinear characteristics of moving vehicles, nonlinear observer of vehicle status is designed to strength robustness of dynamic control system in this paper. A 4-degree-of-freedom nonlinear dynamic model of articulated electric drive vehicle is built as reference model to estimate the state of the articulated vehicle. And by adopting Unscented Kalman Filter (UKF) algorithm, a series of state parameters such as longitudinal velocities of front and rear frames, yaw rate and side-slip angle are estimated. During the test of 60 t articulated electric drive vehicle, 2 inertial navigation modules are installed in the front frame and rear frame respectively and the speed of each electric drive wheel is obtained simultaneously. As the test results suggest, in various working conditions, the algorithm based on UKF is able to accurately estimate the state parameters of articulated vehicle with the estimated error less than 5%. The proposed method is justified to be the theoretical basis and application guidance for articulated vehicle stability control.