Application of Unscented Kalman Filter Algorithm for Assessing the Aero Engine Performance Degradation

Abstract

Kalman Filter and Extended Kalman Filter (EKF) have been widely applied for aero engine performance assessment. Aiming at improving upon the Kalman Filter based methods, this investigation explores applying Unscented Kalman Filter (UKF) algorithm for aero engine performance degradation evaluation. Improvements on the UKF algorithm are made for optimal performance, by adding a factor or adjusting the prediction variance matrix, as well as finding the optimal distribution of Sigma points. The simulation result shows that compared with EKF algorithm and with multi-dimensional degradation, the UKF algorithm proposed in this study improves the performance degradation assessment error by a large margin(33%), while suffering from prolonged numerical time and sensitivity to the initial error.