Acceleration technique for global optimization of a variable cycle engine

Abstract

A variable cycle engine (VCE) is a potential power system for future advanced military and civil aircraft. The involvement of numerous adjustable parameters enables a VCE to meet multiple flight requirements simultaneously; however, it also increases the difficulty of engine design. Global algorithms can be adopted to maximally exploit the performance potential of a VCE while satisfying constraints. However, the optimization of a VCE is a highly constrained and nonlinear problem with high computational cost. In this article, a novel acceleration technique for the global optimization of VCEs is presented. The initial guesses for the iterations of the VCE model were optimized along with the optimization variables to reduce the model call number (MCN). The differential evolution (DE) algorithm was chosen to demonstrate and verify the effectiveness of this acceleration technique. The results show that the technique can significantly reduce the MCN under most conditions without affecting the optimization process. The more rapidly the DE converges, the more significantly the MCN is reduced. In some cases, this technique can help improve the optimization results. Moreover, the technique can be applied to various DE improvement strategies. This technique can also be employed in the performance optimization of other aero engines or similar systems.