%0 Journal Article
%T Helicopter gas turbine engine performance analysis: A multivariable approach
%A Ilan Arush
%A Marilena D Pavel
%J Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
%@ 2041-3025
%D 2019
%R 10.1177/0954410017741329
%X Helicopter performance relies heavily on the available output power of the engine(s) installed. A simplistic single-variable analysis approach is often used within the flight-testing community to reduce flight-test data in order to predict the available output power under various atmospheric conditions. This simplistic approach often results in unrealistic predictions. This paper proposes a novel method for analyzing flight-test data of a helicopter gas turbine engine. The so-called ¡°Multivariable Polynomial Optimization under Constraints¡± method is capable of providing an improved estimation of the engine maximum available power. The Multivariable Polynomial Optimization under Constraints method relies on optimization of a multivariable polynomial model subjected to equalities and inequalities constraints. The Karush¨CKhun¨CTucker optimization method is used with the engine operating limitations serving as inequalities constraints. The proposed Multivariable Polynomial Optimization under Constraints method is applied to a set of flight-test data of a Rolls Royce/Allison MTU250-C20 gas turbine, installed on an MBB BO-105£¿M helicopter. It is shown that the Multivariable Polynomial Optimization under Constraints method can predict the engine output power under a wider range of atmospheric conditions and that the standard deviation of the output power estimation error is reduced from 13£¿hp in the single-variable method to only 4.3£¿hp using the Multivariable Polynomial Optimization under Constraints method (over 300% improvement)
%K Gas turbine
%K multivariable linear regression
%K Karush¨CKhun¨CTucker
%K helicopter performance
%K flight testing
%U https://journals.sagepub.com/doi/full/10.1177/0954410017741329