Affiliation:
1. Aircraft Engine Design Department, Faculty of Aviation Engines , National Aerospace University ‘Kharkiv Aviation Institute’ , 17 Chkalova Street , Kharkiv , Ukraine
Abstract
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.
Reference24 articles.
1. [1] Jaw, L. and Mattingly, J. “Aircraft Engine Controls: Design, System Analysis, and Health Monitoring.” American Institute of Aeronautics and Astronautics, Inc., Reston, USA (2009): p. 378
2. [2] Wang, J., Zhang, W., and Hu, Z. “Model-Based Nonlinear Control of Aeroengines.” Springer Nature Singapore Pvt. Ltd (2022): p. 238.
3. [3] Yepifanov, S. “Aircraft Turbine Engine Automatic Control Based on Adaptive Dynamic Models.” Transactions on Aerospace Research Vol. 4, No. 261 (2020): pp. 61–70.
4. [4] Ibrahem, I.M.A., Akhrif, O., Moustapha, H., and Staniszewski, M. “Nonlinear Generalized Predictive Controller Based on Ensemble of NARX Models for Industrial Gas Turbine Engine.” Energy Vol. 230, No. 1 (2021): p. 120700, 14.
5. [5] Kim, S. “A New Performance Adaptation Method for Aero Gas Turbine Engines Based on Large Amounts of Measured Data.” Energy Vol. 221 (2021): p. 119863, 15.