Variable rotor speed and active blade twist for civil rotorcraft: Optimum scheduling, mission analysis, and environmental impact

摘要

The concepts of variable rotor speed and active blade twist constitute promising technologies in terms of improving the operational performance and environmental impact of rotorcraft. Modern civil helicopters typically operate using nearly constant main and tail rotor speeds throughout their operational envelope. However, previous research has shown that decreasing the main rotor speed within salient points of the operational envelope can result in a notable reduction of rotor power requirement, resulting in more efficient aircraft. This work aims to develop an integrated approach able to evaluate the potential improvements in fuel economy and environmental impact through optimum implementation and scheduling of variable rotor speed combined with active blade twist. A comprehensive rotorcraft analysis method is utilized, comprising models applicable to flight dynamics, rotor blade aeroelasticity, engine performance, gaseous emission prediction, and flight path analysis. A holistic optimization strategy comprising methods for Design of Experiment (DOE), Gaussian Process-based (GP) surrogate-modeling, and genetic optimization is developed. The combined framework is used to predict globally optimum variable rotor speed and active blade twist schedules resulting in minimum fuel consumption. The overall method is employed to assess the impact of the investigated concepts for a representative Twin-Engine Light (TEL) helicopter operating within realistic mission scenarios. The optimizations carried out suggest that variable rotor speed combined with active blade twist may result in mission fuel consumption and nitrogen oxides emission (NOx) reductions of the order of 5% and 8%, relative to the fixed rotor speed case. The developed method constitutes an enabling technology for the investigation of novel technologies at multiple levels of assessment including aircraft-engine and mission levels. (C) 2019 Elsevier Masson SAS. All rights reserved.