Keywords
UAV, drone, hexacopter, heavy-lift, multifungtion drone
Document Type
Article
Abstract
Previous research has proven that the use of Unmanned Aerial Vehicles (UAVs) can increase the efficiency of human work. However, the design of the usefulness of UAV is considered to be limited. This limitation, for example, is that the UAV's lifting capacity is only capable of lifting 3-5 kilograms of load on average. In addition, the main material of the UAV frame also uses carbon fiber produced by build-up factories abroad, this makes the UAV design less economical. Furthermore, this study discusses the development of the UAV's lifting capacity of 25 kilograms to be able to lift the pesticide liquid load and considers the economic value. The hexacopter type multicopter UAV design was chosen in this study, equipped with 6 main propulsion rotors capable of carrying out its main task of lifting heavy loads, compared to the multicopter type of fewer than 6 rotors. The design is carried out by calculating the lifting force and analyzing the strength structure of the frame material with the help of AutoDesk Inventor software. The final result of the study was that the aluminum-based heavy-lift hexacopter drone was able to support heavy loads, as evidenced by structural analysis simulations resulting in a safety factor value of 1.67 ul, equipped with a 120KV rotor, 23x88 inch propeller, and 6S lipo battery 16,000 mAh, with a total weight of the frame 15kg drone flying for 19 minutes, with an additional 10kg of load the drone can fly for 6 minutes. This research can be developed by adding a nozzle or griper so that it can lift the pesticide spraying tank on a large enough agricultural land.
First Page
1
Last Page
9
Page Range
2024-09-01
Issue
1
Volume
7
Digital Object Identifier (DOI)
10.21831/elinvo.v7i1.41097
Source
https://journal.uny.ac.id/index.php/elinvo/article/view/41097
Recommended Citation
U. M. Arief et al., "Design and Development of Aluminum Frame Unmanned Aerial Vehicle Hexacopter Configuration to Support Heavy Payload,", vol. 7, no. 1, pp. 1 - 9, Dec 2022.
The definitive version is available at https://doi.org/10.21831/elinvo.v7i1.41097
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