Aiming at problem that components of aircraft engine will degrade slowly during its life cycle

but current linear model modeling methods of engine cannot meet requirement of precision for the whole life cycle

which leads to the fact that estimation errors of filtering algorithm for health parameters increases with flight cycles

an adaptive fitting method is proposed to establish state variable model（ SVM） and Kalman filter is designed for health parameters estimation. The method uses health parameter estimation value to realtime update related coefficient matrices in the last sampling period

so as to improve precision of the linear model. Linear variable parameter model is established for a commercial aircraft engine

at design cruise point on the basis of component level model. And by applying similarity transformation

at several flight state points

performance degradations process are digitally simulated. The simulation results reveal that KF based on the proposed modeling method greatly improves the estimation precision of health parameters and also has good real-time ability.