<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>One of the most perspective directions of aircraft engine development is related to implementing adaptive automatic electronic control systems (ACS). The significant elements of these systems are algorithms of matching of mathematical models to actual performances of the engine. These adaptive models are used directly in control algorithms and are a combination of static and dynamic sub-models. This work considers the dynamic sub-models formation using the Least Square method (LSM) on a base of the engine parameters that are measured in-flight. While implementing this function in the (ACS), the problem of checking the sufficiency of the used information for ensuring the required precision of the model arises. We must do this checking a priori (to determine a set of operation modes, the shape of the engine test impact and volume of recorded information) and a posteriori. Equations of the engine models are considered. Relations are derived that determine the precision of parameters of these models’ estimation depending on the precision of measurement, the composition of the engine power ratings, and durability of observations, at a stepwise change of fuel flow. We present these relations in non-dimensional coordinates that make them universal and ready for application to any turboshaft engine.</p>
</abstract>

One of the most perspective directions of aircraft engine development is related to implementing adaptive automatic electronic control systems (ACS). The significant elements of these systems are algorithms of matching of mathematical models to actual performances of the engine. These adaptive models are used directly in control algorithms and are a combination of static and dynamic sub-models. This work considers the dynamic sub-models formation using the Least Square method (LSM) on a base of the engine parameters that are measured in-flight. While implementing this function in the (ACS), the problem of checking the sufficiency of the used information for ensuring the required precision of the model arises. We must do this checking a priori (to determine a set of operation modes, the shape of the engine test impact and volume of recorded information) and a posteriori. Equations of the engine models are considered. Relations are derived that determine the precision of parameters of these models’ estimation depending on the precision of measurement, the composition of the engine power ratings, and durability of observations, at a stepwise change of fuel flow. We present these relations in non-dimensional coordinates that make them universal and ready for application to any turboshaft engine.

Development of Turboshaft Engine Adaptive Dynamic Model: Analysis of Estimation Errors

Aircraft Engine Design Department, Faculty of Aviation Engines

National Aerospace University ‘Kharkiv Aviation Institute’

Transactions on Aerospace Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

One of the most perspective directions of aircraft engine development is related to implementing adaptive automatic electronic control systems (ACS). The...

Development of Turboshaft Engine Adaptive Dynamic Model: Analysis of Estimation Errors

Data publikacji: 16 gru 2022

Zakres stron: 59 - 71

Otrzymano: 24 sty 2022

Przyjęty: 10 paź 2022

DOI: https://doi.org/10.2478/tar-2022-0024

Słowa kluczowe
turbine engine, turboshaft, gas generator, dynamic model, engine time constant, identification, estimation error, design of experiment

© 2022 Sergiy Yepifanov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Development of Turboshaft Engine Adaptive Dynamic Model: Analysis of Estimation Errors

Data publikacji: 16 gru 2022

Zakres stron: 59 - 71

Otrzymano: 24 sty 2022

Przyjęty: 10 paź 2022

DOI: https://doi.org/10.2478/tar-2022-0024

Słowa kluczoweturbine engine, turboshaft, gas generator, dynamic model, engine time constant, identification, estimation error, design of experiment

© 2022 Sergiy Yepifanov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Słowa kluczowe
turbine engine, turboshaft, gas generator, dynamic model, engine time constant, identification, estimation error, design of experiment