IEEE Access (Jan 2020)

Optimization and Analysis of Hybrid Electric System for Distributed Propulsion Tilt-Wing UAV

  • Cheng He,
  • Yuhong Jia,
  • Dongli Ma

DOI
https://doi.org/10.1109/ACCESS.2020.3044449
Journal volume & issue
Vol. 8
pp. 224654 – 224667

Abstract

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Hybrid electric distributed propulsion tilt-wing UAVs show unlimited application prospects due to their high propulsion efficiency and vertical take-off and landing capabilities. Aiming at the power requirements of distributed propulsion tilt-wing UAVs, this article presents an optimization design method for series hybrid electric propulsion systems suitable for this type of aircraft. Based on the flight conditions and constraints of various modes, the power demand models for distributed propulsion tilt-wing UAVs are established for vertical flight mode, transition mode, and forward flight mode. The hybrid electric power solving models of each component of the series hybrid electric system are established by analyzing the series hybrid power architecture and power transmission paths. The hybrid electric system weight model is mainly decomposed into the weight model of each component and the fuel consumption model. Based on power demand and energy demand, a mass model of components such as batteries, engines, generators, power management and distribution systems are established. Besides, the fuel consumption characteristic curve of the scaled engine is established using the Willans line formulation, and the fuel consumption calculation in the full flight profile is completed. The optimization of the series hybrid electric system of a 200kg-class distributed propulsion tilting wing UAV under two mission profiles of urban freight and mountain freight and the sensitivity of the optimized results to performance are presented. The results show that the proposed method can sensitively capture the significant influence of the adjustment of the mission profile and the changes in the performance requirements of each flight phase, and adapt to various application scenarios.

Keywords