基于遗传算法的飞翼布局电动无人机优化设计
首发时间:2012-06-04
摘要: 对采用正弯度翼型的飞翼布局电动无人机进行了计算研究。本文建立无人机电池、电机和结构重量模型,机翼通过后掠、几何扭转以及襟翼、升降副翼的合理配置以减小纵向配平阻力,同时融合CMARC气动力计算和纵向稳定性分析,确定一架航时为4小时的飞翼布局小型手掷电动无人机总体参数。以小尺寸轻重量为优化目标,使用遗传算法对无人机总体参数进行优化。计算结果表明:相对于反弯度翼型,使用正弯度翼型的飞翼布局无人机能减小无人机质量和尺寸,改善其起降和续航性能。
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Optimized Design for Flying-wing Electric-powered UAV Based on Genetic Algorithm
Abstract:The flying-wing electric-powered UAV based on cambered airfoil is studied. In this paper, the battery, motor, and structure weight model of UAV is presented. Longitudinal trimmed drag is reduced by the swept wing, geometrical twist as well as optimized dimension of flap and elevon. The CMARC is incorporated into the optimization procedure to compute the aerodynmics and longitudinal stability parameters. Configuration parameters of a hand-launched flying-wing electric-powered UAV based on 4 hours endurance are confirmed. Then, the configuration parameters are optimized using the genetic algorithm to minimize mass and size. In comparison with the flying wing UAV with reflex airfoil, the mass and size with cambered airfoil are decreased. Meanwhile, the taking-off, landing and endurance performance are improved.
Keywords: electric-powered UAV flying-wing genetic algarithm (GA)
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