Cessna Citation X Engine Model Experimental Validation

Paul Alexandre A. Bardella, Ruxandra Mihaela Botez, and Pierre Pageaud

Keywords

Engine, Turbofan, Identification, Flight Test, Cessna Citation X

Abstract

The aviation industry is motivated to develop and validate new aircraft models for the prediction of engine performance. These models are used in the preliminary aircraft design in order to predict its engines performance. The purpose of this study is to design an accurate model of the fan and compressor engine components. This model will then be integrated in a full engine model based on a component modeling approach. Several methods already exist to model compressing components. Among them, the stage-stacking method is used in this paper. This method can be used to predict the compressor performance but also its deterioration (ex: “fouling”). In both cases, the principle is the same. Each stage is separated, and the first stage outputs are used for the next stage as inputs until the last stage is reached, when the final outputs are acquired. A Cessna Citation X Level D Research Flight Simulator designed by CAE Inc. is used to sample the data needed to identify and validate the engine models elaborated for the whole flight envelope. Level D is the highest level of certification given by the FAA for the flight dynamics. Thus the simulator is used as real aircraft flight dynamics data. Different flight tests were performed to mesh the flight envelope for different flight conditions (Mach numbers from 0 to 0.92; altitude from 0 to 50000ft and Throttle Lever Angle,TLA, from “idle” to “max” in degrees). Nonetheless, the stage stacking method needs information which is not always available, such as the blade angle. A “grey box” approach was chosen. The unmeasurable parameters were identified in order to tune the model, and thus to reduce the global error between the model and the simulation data. A “black box” approach was also with an optimisation algorithm to approximate the outputs as polynomial functions of the inputs. In both cases the results were found to be accurate.

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