A Simulation Study of Turbofan Engine Deterioration Estimation Using Kalman Filtering Techniques

Lambert, Heather H. (1991) A Simulation Study of Turbofan Engine Deterioration Estimation Using Kalman Filtering Techniques. Technical Report NASA TM-104233, Research Engineering, NASA Dryden Flight Research Center.

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Abstract

Current engine control technology is based on fixed control parameter schedules derived for a nominal production engine. Deterioration of the engine components may cause off-nominal engine operation. The result is an unnecessary loss of performance, because the fixed schedules are designed to accommodate a wide range of engine health. These fixed control schedules may not be optimal for a deteriorated engine. This problem may be solved by including a measure of deterioration in determining the control variables. These engine deterioration parameters usually cannot be measured directly but can be estimated. This document presents a Kalman filter design for estimating two performance parameters that account for engine deterioration: high- and low- pressure turbine delta efficiencies. The delta efficiency parameters model variations of the high- and low-pressure turbine efficiencies from nominal values. The filter was evaluated using a nonlinear simulation of the F100 engine model derivative (EMD) engine. This work found that at the model design condition, known high-pressure turbine delta efficiencies of –2.5 percent and low-pressure turbine delta efficiencies of –1.0 percent can be estimated with an accuracy of ±0.25 percent efficiency with a Kalman filter. If both the high- and low-pressure turbine are deteriorated, then delta efficiencies of –2.5 percent to both turbines can be estimated with the same accuracy.

EPrint Type:	NASA Technical Memorandum
Keywords:	Engine deterioration, Engine health, Engine models, Estimation, Identification, Kalman filter
Subjects:	(01 - 09) Aeronautics: (07) Aircraft Propulsion And Power Aircraft/Project: F-15
ID Code:	300
Deposited On:	28 July 2004
Additional Information:	47 pages.