Automated Design Optimization of a Mono Tiltrotor in Hovering and Cruising States

Abstract

A mono tiltrotor (MTR) design which combines concepts of a tiltrotor and coaxial rotor is presented. The aerodynamic modeling of the MTR based on blade element momentum theory (BEMT) is conducted, and the method is fully validated with previous experimental data. An automated optimization approach integrating BEMT modeling and optimization algorithms is developed. Parameters such as inter-rotor spacing, blade twist, taper ratio and aspect ratio are chosen as design variables. Single-objective (in hovering or in cruising state) optimizations and multi-objective (both in hovering and cruising states) optimizations are studied at preset design points; i.e., hovering trim and cruising trim. Two single-objective optimizations result in different sets of parameter selections according to the different design objectives. The multi-objective optimization is applied to obtain an identical and compromised selection of design parameters. An optimal point is chosen from the Pareto front of the multi-objective optimization. The optimized design has a better performance in terms of the figure of merit (FM) and propulsive efficiency, which are improved by 7.3% for FM and 13.4% for propulsive efficiency from the prototype, respectively. Further aerodynamic analysis confirmed that the optimized rotor has a much more uniform load distribution along the blade span, and therefore a better aerodynamic performance in both hovering and cruising states is achieved.

Multidisciplinary Design Optimization for a Solar-Powered Exploration Rover Considering the Restricted Power Requirement

“…Figure 12 shows a Pareto front that can be an optimal solution at any point. From this figure, it should be noted that maximizing the tractive coefficient (related to the drawbar pull) will minimize the power margin (affected by the wheel resistance torque) under the design constraints [72]. In this study, an optimal design is to be created from the maximal tractive coefficient without extreme solutions, as marked in Figure 12.…”