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Delivery Drone Driving Cycle

机译:送货无人驾驶循环

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摘要

Large companies such as Amazon and Google are currently testing deliveries using unmanned drones, intending to use these drones on the market. Topics tackled in this field of research include object collision routing optimization, delivery routing optimization, battery management optimization, and the addition of solar panels on the drones. Little publicly available research has been found to have been conducted on developing the methods to optimize the powertrain of the drones to maximize their delivery radii through modifying their electric motor and propeller parameters. In working towards that goal, this paper puts forth a delivery drone driving cycle simulation written in MATLAB with which to monitor their performance and fine-tune their properties. The driving cycle has been written to accommodate unmanned drones that use any number of propellers and perform vertical take-off and landing maneuvers. This driving cycle algorithm iteratively runs through multiple driving profiles to find the one which produces the maximal delivery radius for the drone. A data processing tool for polynomial interpolation, which is also written in MATLAB, is developed to manipulate the electric motor and propeller data into usable states for the simulation. For the tested drone configurations, no discernible pattern was noticed in the ideal power throttle needed to reach cruise altitude most efficiently. During cruise, an ideal pitch between 27 to 47 degrees which allowed them to displace horizontally while spending the least amount of energy per meter was found for all configurations.
机译:亚马逊和谷歌等大公司目前正在使用无人机无人机测试交付,打算在市场上使用这些无人机。在此研究领域中解决的主题包括对象碰撞路由优化,交付路由优化,电池管理优化以及在无人机上添加太阳能电池板。已经发现在开发方法以优化无人机动力系以最大化其电动机和螺旋桨参数来最大限度地进行公开可用的研究。在努力实现这一目标时,本文提出了在Matlab中写入的送货无人机驾驶循环仿真,以监测其性能和微调其性质。已经写入驾驶周期以适应使用任何数量螺旋桨的无人驾驶机构,并执行垂直起飞和着陆机动。该驱动周期算法迭代地运行多个驾驶配置文件,以找到为无人机产生最大递送半径的轨道。开发了一种用于MATLAB中的多项式插值的数据处理工具,用于操纵电动机和螺旋桨数据以进行模拟的可用状态。对于测试的无人机配置,在最有效地达到巡航高度所需的理想功率节流阀中没有发现可辨别的模式。在巡航期间,在27至47度之间的理想间距,允许它们水平地拆除,同时为所有配置发现每米的最少的能量。

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