Modeling of a two-axle rail vehicle for state estimation

Abstract

A two-axle rail vehicle having solid axle wheel-sets is developed by using Kalman filter state estimator. Approximately 18 states (from all the 8 inertial measurements) are observed by developing a Kalman filter. A total of five gyroscopes and three accelerometers calibrate the lateral acceleration, yaw velocity of the vehicle and two wheel-sets roll velocity. All the vehicle states are observed by formulating the Kalman filter, moreover, the Kalman filter is also used to calculate the different parameters like cant angle and radius of the curvature of the track. The design of the rail vehicle is validated by comparing the actual results with the same from computer simulations. The simulation also helps to develop an optimal and novel controller to assess the performance of the design of an active steering system.