Optimization of thin electric propeller using physics-based surrogate model with space mapping

Abstract

The propulsion system greatly effects the performance of small electric powered Unmanned Aerial Vehicles (UAV). The propeller is one of the key elements of an electric propulsion system. The present research aims to optimize the propeller shape by utilizing the physics-based surrogate modeling strategy along with a space mapping method. A quasi-global construction is made that perceptively links a low-fidelity (coarse) model and a high-fidelity (fine) model, thus avoiding the direct optimization of the fine model. The space mapping utilizes a parameter extraction process that assist the surrogate model to locally realign itself with the fine model. For coarse model, an open source propeller analyses and design program (QPROP) is used. This program uses an extension of the classical blade element formulation. The fine model is based on the computational fluid dynamics analysis utilizing the finite-volume discretization of the Reynolds-averaged Navier–Stokes equations. The computed results have been verified by comparing them with the available propeller performance data. After a successful validation, geometric parameters for the propeller are varied to study their effect on performance and carry out parametric sensitivity analysis. The selected design variables control the section airfoil shape and the propeller geometry. The optimized design has been achieved with few iterations of the fine model reducing the overall computational cost of optimization process. The results indicate that the space mapping surrogate modeling is an effective strategy for propeller shape optimization.