Dual estimation of lateral analysis for railway vehicle wheelset to control disturbance for smooth running

Abstract

The lateral aspects of railway vehicle wheelset have a significant impact on railway wheelset dynamic systems. Lateral analysis usually causes wheelset slippage from the track resulting insufficient adhesion which can lead to creep. Significant disturbances are mostly caused in lateral direction due to speed. This paper uses the dual Kalman filter strategy to deal with noise issues and thus minimizes the error ratio during observation. A single Kalman filter reduces errors to a minimum extent while the second estimator decreases the maximum available chance of error. Using a third estimator provides no further improvement over the dual Kalman filter implementation.