Method of pre-project selection of components for fpv uavs the quadropter type according to the set values of thrust, speed and flight time

Abstract

Purpose. Develop a methodology for the pre-project selection of quadcopter-type UAV components for the creation of drones based on the specified criteria.

Methodology. Mathematical analysis and modeling.

Findings. The paper presents a comprehensive framework aimed at facilitating the rapid assembly of customizable multirotor unmanned aerial vehicles (MR-UAVs) tailored to specific mission requirements, all without the need for tools. This modular approach encompasses the development, implementation, and evaluation of a structured process that guides operators through selecting hardware components such as sensors, actuators, propellers, motors, batteries, and electronic speed controllers. This meticulous selection process is pivotal in achieving the desired flight characteristics of the MR-UAV. Furthermore, a software tool has been devised to streamline the equipment selection process and accurately compute flight time. The flight time calculation algorithm, rooted in data obtained from brushless motor and propeller analyses conducted using a traction stand/dynamometer, has undergone rigorous testing to ensure reliability and precision. The framework itself comprises five distinct modules: controller, transmission, video, communication, and payload. These modular components afford users the flexibility to mix and match according to the demands of their specific application, enabling the swift assembly of an MR-UAV optimized for the task at hand. To validate the efficacy of the framework, a prototype was constructed and subjected to rigorous testing, confirming the soundness of the design. Notably, the versatility of this framework is exemplified through the creation of three distinct modular MR-UAV profiles. These profiles cater to diverse applications: surveillance, emphasizing extended flight time; delivery, prioritizing larger payload capacity; and a hybrid configuration allowing seamless transition between battery power sources mid-flight. In essence, this paper not only introduces a modular framework for MR-UAV assembly but also underscores its practicality and adaptability through real-world implementation and testing across varied mission profiles.

Originality.  For this section of the abstract should determining the most important results that reflect originality of work. The algorithm proposed in the article is based on an approach that allows adapting MR-UAVs at a higher level than previous systems. The infrastructure allows the user to configure flight characteristics (flight time, speed, maximum payload), as well as sensors and communication channels (video and data link) according to the requirements of a specific operation.

Practical value. To facilitate the process of selecting hardware components for frame modules, the paper presents an algorithm for estimating flight time, which is included in the process of building modular profiles. The algorithm has been tested and an average accuracy of 98.94% has been achieved for hover time-of-flight estimation. The design of the software is presented. This tool allows developers to analyze brushless motor and propeller data (obtained from the thrust stand), evaluate how gross weight and battery selection affect the MR-UAV (in terms of flight time, thrust-to-weight ratio, and maximum payload), and optimizes the process development of MR-UAV.