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Thrust modelling of a target drone engine with nonlinear least – squares estimation based on series expansions

Thrust modelling of a target drone engine with nonlinear least – squares estimation based on... The purpose of this study is to build a high accuracy thrust model under various small turbojet engine shaft speeds by using robust, ordinary, linear and nonlinear least squares estimation methods for target drone applications.Design/methodology/approachThe dynamic shaft speeds from the test experiment of a target drone engine is conducted. Then, thrust values are calculated. Based on these, the engine thrust is modeled by robust linear and nonlinear equations. The models are benefited from quadratic, power and various series expansion functions with several coefficients to optimize the model parameters.FindingsThe error terms and accuracy of the model are given using sum of squared errors, root mean square error (RMSE) and R-squared (R2) error definitions. Based on the multiple analyses, it is seen that the RMSE values are no more than 17.7539 and the best obtained result for robust least squares estimation is 15.0086 for linear at all cases. Furthermore, the R2 value is found to be 0.9996 as the highest with the nonlinear Fourier series expansion model.Originality/valueThe motivation behind this paper is to propose robust nonlinear thrust models based on power, Fourier and various series expansion functions for dynamic shaft speeds from the test experiments. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Aircraft Engineering and Aerospace Technology: An International Journal Emerald Publishing

Thrust modelling of a target drone engine with nonlinear least – squares estimation based on series expansions

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1748-8842
eISSN
1748-8842
DOI
10.1108/aeat-08-2021-0236
Publisher site
See Article on Publisher Site

Abstract

The purpose of this study is to build a high accuracy thrust model under various small turbojet engine shaft speeds by using robust, ordinary, linear and nonlinear least squares estimation methods for target drone applications.Design/methodology/approachThe dynamic shaft speeds from the test experiment of a target drone engine is conducted. Then, thrust values are calculated. Based on these, the engine thrust is modeled by robust linear and nonlinear equations. The models are benefited from quadratic, power and various series expansion functions with several coefficients to optimize the model parameters.FindingsThe error terms and accuracy of the model are given using sum of squared errors, root mean square error (RMSE) and R-squared (R2) error definitions. Based on the multiple analyses, it is seen that the RMSE values are no more than 17.7539 and the best obtained result for robust least squares estimation is 15.0086 for linear at all cases. Furthermore, the R2 value is found to be 0.9996 as the highest with the nonlinear Fourier series expansion model.Originality/valueThe motivation behind this paper is to propose robust nonlinear thrust models based on power, Fourier and various series expansion functions for dynamic shaft speeds from the test experiments.

Journal

Aircraft Engineering and Aerospace Technology: An International Journal – Emerald Publishing

Published: Jan 2, 2023

Keywords: Aircraft; Nonlinear least squares; Turbojet; Microturbo target drone; Series expansion; Thrust modeling

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