Estimation of Thrust and Health Parameters for Jet Engines
Doktorsavhandling, 2011

An advanced turbofan engine control system would benefit from an accurate thrust and engine performance estimate. Unfortunately, there is to date no reliable in-flight thrust measurement sensors available. The engine performance and some of the critical components will degrade with usage, which is usually described by the so-called health parameters of the individual engine components. These health parameters may also be of use in an advanced engine control system. The system could diagnose faults, recognize performance deterioration, and might even change the power demand to recover some lost thrust within the physical constraints of the engine, even with degraded capability. In present control systems, the fan speed as well as other system outputs are controlled by the nozzle area and the fuel flow. The control references are set to promote the desired engine thrust as well as low fuel consumption with safe engine operation. A thrust estimate may be used instead of a non-existing thrust measurement as the target of control in a outer loop, when the control signal represents set-points for the inner loop controller. This thesis analyzes some approaches to the construction of such thrust and health parameter estimators, in this thesis referred to as filters. The filters are to be used for in-flight estimation in real-time using the most common on-board sensors, ambient conditions and actuator information. The filters are model-based where both fictitious and real engine models have been used in the evaluation. The results indicate that a thermodynamic model-based thrust observer has sufficient accuracy performance. Usually module performance analysis relies on steady-state measurements from a single operating point to evaluate the level of engine deterioration. The major difficulty associated with this estimation problem comes from its under-determined nature. This thesis contributes in indicating that there are better strategies.

Thrust estimation

Kalman filtering

Gas turbine performance estimation

Reduced order observers

Gas path analysis

Opponent: Keith Glover


Mattias Henriksson

Chalmers, Signaler och system, System- och reglerteknik


Informations- och kommunikationsteknik






Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie


Opponent: Keith Glover

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