Fusion Prediction of Aero-engine Performance Parameters based on Cubature Kalman Filter

Accurate performance parameter prediction plays an important role in improving the operation performance, service safety and the accuracy of aircraft health management and maintenance strategies. Aiming at the problem of engine performance parameter prediction, a fusion prediction method based on Cubature Kalman Filter (CKF) is proposed in this paper. Firstly, the mechanism model of aero-engine based on T-MATS is established, and then the Cubature Kalman Filter (CKF) is used to fuse the state data of the aero-engine model with the observed data of sensors. The model was simulated by using foreign engine test data set, and the results show that compared with the Unscented Kalman filter (UKF) fusion, the error of the data after CKF fusion is smaller and the robustness is better.