An unscented Kalman filter based velocity estimation method for articulated steering vehicle using a novel dynamic model

Abstract

This paper presents a novel velocity estimation method for an articulated steering vehicle to improve the automation and safety of articulated steering vehicle. The estimation method process is done in three steps: First, the articulated steering vehicle's tire forces are calculated separately against articulated steering vehicle's asymmetric tire load transfers. Then the tire forces are used to build a concise dynamic model, which only needs to consider the single centroid's dynamics in a fixed direction of the vehicle body. Finally, an unscented Kalman filter estimator is developed further based on the articulated steering vehicle dynamics model for velocity estimation. The main contribution of this paper to the related literature lies in two aspects. On the one hand, by converting the velocity vectors of each vehicle body to a fixed coordinate system, a concise dynamic model is built to avoid complex calculations and high sensor costs. On the other hand, an additional moment equilibrium equation is introduced to assist the simplified estimator in calculating the asymmetric tire dynamics of articulated steering vehicle, which ensures the accuracy and universality of the method. The simulation results from ADAMS/MATLAB indicate that the proposed model can effectively reflect the dynamics of articulated steering vehicle even under obvious load transfer. In addition, the developed unscented Kalman filter estimator can obtain accurate and robust estimation results in several typical vehicle manoeuvres.