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

Aziz Kaba (Faculty of Aeronautics and Astronautics, Eskisehir Technical University, Eskisehir, Turkey)
Ece Yurdusevimli Metin (Faculty of Aeronautics and Astronautics, Eskisehir Technical University, Eskisehir, Turkey)
Onder Turan (Faculty of Aeronautics and Astronautics, Eskisehir Technical University, Eskisehir, Turkey)

Aircraft Engineering and Aerospace Technology

ISSN: 0002-2667

Article publication date: 14 June 2022

Issue publication date: 2 January 2023

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Abstract

Purpose

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/approach

The 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.

Findings

The 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/value

The 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.

Keywords

Citation

Kaba, A., Yurdusevimli Metin, E. and Turan, O. (2023), "Thrust modelling of a target drone engine with nonlinear least – squares estimation based on series expansions", Aircraft Engineering and Aerospace Technology, Vol. 95 No. 1, pp. 38-52. https://doi.org/10.1108/AEAT-08-2021-0236

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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