Kalman filter for the state estimation of a 2-AXLE railway vehicle

Abstract

This paper presents the development of a state observer for a 2-axle railway vehicle with solid axle wheelsets. A plan view model of the vehicle is presented and a Kalman filter is developed to estimate 18 states from 8 inertial measurements. The required measurements are the lateral acceleration and yaw velocity of the vehicle body and the same measurements plus the roll velocity for the two wheelsets, requiring three accelerometers and five gyros. The Kalman filter is formulated in such a way that it not only estimates all the vehicle states, but also calculates parameters such as curve radius and cant of the railway track on which the vehicle is travelling. Computer simulations are used to verify the design and to assess its performance together with an optimal controller developed for active steering of the wheelsets.