Turboshaft engine self-adaptive model building method based on modified Broyden algorithm to solve equation set

Abstract

The present invention discloses a turboshaft engine self-adaptive model building method based on a modified Broyden algorithm to solve an equation set. The method comprises: matching a self-adaptive model with a real engine by forming and solving the equation set. A non-linear equation set is established according to a principle in which a model outputs a tracked real engine output and in combination with a coacting equation between engine parts, and the equation set is solved by using a modified Broyden algorithm, to acquire a part performance degradation parameter and a turboshaft engine part level model guess value. The modified Broyden algorithm is based on a Broyden quasi-newton method and is combined with a computation divergence determination and correction mechanism, so that computation accuracy and real-time performance are improved. The performance degradation parameter acquired by solving the equation set is introduced into a turboshaft engine part level model as an adjustable parameter, so that the model has a self-adaptive capability.

Description

technical field [0001] The invention belongs to the field of system control and simulation in aerospace propulsion theory and engineering, and particularly relates to a method for establishing an adaptive model of a turboshaft engine based on an improved Broyden algorithm for solving equations. Background technique [0002] Aero-engine adaptive model plays a very important role in the field of modern aero-engine intelligent control, performance optimization, parameter prediction and fault diagnosis. As early as the 1980s, foreign scholars used the Kalman filter to estimate the performance degradation of engine components based on the measurable parameters of the engine, and used the component performance degradation amount as an adjustable parameter to act on the engine adaptive model. Since then, the research on the engine adaptive model has been Continue to expand. [0003] The aero-engine adaptive model mainly adopts the component-level mathematical model, and establishe...

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Problems solved by technology

However, the adaptive model obtained by this method can only track the steady-state value of the engine, and the design process of the Kalman filter needs to establish a linear model of the state variable with small deviations, which cannot cover the entire flight envelope of the aero-engine with strong nonlinearity. line, so the degradation parameter estimation ability at the remaining operating points is poor, so it is necessary to carry out research on a new adaptive model building method

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