This paper proposes an improved hybrid Kalman filter(IHKF) for in-flight aircraft engine performance estimation. It’s a special hybrid structure of nonlinear on-board engine model(NOBEM) and piecewise linear Kalman filter(PWKF). The outputs of NOBEM is regarded as the baseline of PWKF, while its performance deterioration factors(PDF) regarded as the augmented state vector of PWKF is on-line estimated by the deviation of measured outputs, and fed back to NOBEM which can be on-line updated next time. In addition, the finite state machine logic of work mode has been established, which can make the IHKF work better. By this approach applied to a turbofan engine, a series of simulation results show that the model can estimate the real engine performance effectively in the whole flight envelope, different engine states and severe performance deterioration condition, which lays the foundation for intelligent engine control(IEC), performance seeking control(PSC) and inflight fault detection, isolation and accommodation (FDIA).
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