Energy Efficiency of Small-Scale UAVs

A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Aeronautics".

Deadline for manuscript submissions: closed (1 July 2022) | Viewed by 20333

Special Issue Editors


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Guest Editor
Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Interests: multiagent systems; distributed control; shared control; wireless sensor networks; UAV-based applications: search and rescue; construction automation; surveillance; wireless communications; parcel delivery
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Special Issue Information

Dear Colleagues,

Over the past few decades, interest in unmanned aerial vehicles (UAVs) has been increasing significantly, with research efforts spanning commercial, industrial, and governmental domains. UAVs have demonstrated uses in but not limited to package delivery, surveillance, inspection, precision agriculture, border control, criminal investigations, search and rescue, weather measurement and forecasting, and disaster relief. The potential uses are remarkably diverse, and as UAV technology becomes more accessible, UAVs will continue to be used in new and surprising ways.

Unlike military UAVs, most commercial UAVs are powered on the on-board battery, which is extremely limited in capacity. Commercially available off-the-shelf UAV products can only fly for about half an hour. This prevents their usage in applications requiring long-time operations. Though improving the battery efficiency and capacity increases the flight time, the improvement room is small if there is no breakthrough in battery technology. Alternatives are needed to enable small-scale UAVs to fly longer.

This Special Issue addresses a broad list of topics related to the energy issue of small-scale UAVs. Papers related but not limited to the following topics are welcome:

  • Trajectory planning and control of UAVs aiming at optimizing energy efficiency;
  • Energy-efficient formation and coordination of UAV swarms;
  • Deployment of charging stations;
  • Collaboration between UAVs and ground vehicles;
  • Design, flight test, and performance monitoring of solar-powered UAVs;
  • Applications of solar-powered UAVs.

Dr. Hailong Huang
Dr. Chao Huang
Guest Editors

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Keywords

  • energy efficiency
  • trajectory planning
  • trajectory optimization
  • surveillance
  • payload delivery
  • wireless communication
  • flight test
  • electronics hardware design
  • solar power system

Published Papers (5 papers)

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Research

18 pages, 7958 KiB  
Article
Range-Based Reactive Deployment of a Flying Robot for Target Coverage
by Mingyang Lyu, Yibo Zhao and Hailong Huang
Aerospace 2022, 9(11), 731; https://doi.org/10.3390/aerospace9110731 - 20 Nov 2022
Viewed by 1548
Abstract
Flying robots, also known as drones and unmanned aerial vehicles (UAVs), have found numerous applications in civilian domains thanks to their excellent mobility and reduced cost. In this paper, we focus on a scenario of a flying robot monitoring a set of targets, [...] Read more.
Flying robots, also known as drones and unmanned aerial vehicles (UAVs), have found numerous applications in civilian domains thanks to their excellent mobility and reduced cost. In this paper, we focus on a scenario of a flying robot monitoring a set of targets, which are assumed to be moving as a group, to which the sparse distribution of the targets is not applicable. In particular, the problem of finding the optimal position for the flying robot such that all the targets can be monitored by the on-board ground facing camera is considered. The studied problem can be formulated as the conventional smallest circle problem if all the targets’ locations are given. Because it may be difficult to obtain the locations in practice, such as in Global Navigation Satellite Systems (GNSS) dined environments, a range-based navigation algorithm based on the sliding mode control method is proposed. This algorithm navigates the flying robot toward the farthest target dynamically, using the estimated robot–target distances from the received signal strength, until the maximum robot–target distance cannot be further reduced. It is light computation and easily implementable, and both features help to improve the energy efficiency of the flying robot because no heavy computation is required and no special sensing device needs to be installed on the flying robot. The presented solution does not directly solve the smallest circle problem. Instead, our proposed method dynamically navigates the flying robot to the center of the group of targets using the extracted distance information only. Simulations in Matlab and Gazebo have been conducted for both stationery and mobile targets to verify the effectiveness of the proposed approach. Full article
(This article belongs to the Special Issue Energy Efficiency of Small-Scale UAVs)
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19 pages, 5931 KiB  
Article
Fuzzy Logic-Based Energy Management Strategy of Hybrid Electric Propulsion System for Fixed-Wing VTOL Aircraft
by Yingtao Zhu, Bingjie Zhu, Xixiang Yang, Zhongxi Hou and Jianan Zong
Aerospace 2022, 9(10), 547; https://doi.org/10.3390/aerospace9100547 - 25 Sep 2022
Cited by 2 | Viewed by 1918
Abstract
An energy management strategy for a series hybrid electric propulsion system designed for a fixed-wing vertical take-off and landing (VTOL) aircraft is presented in this paper. The proposed method combines an ideal operating line (IOL) and fuzzy logic. Fuzzy logic is used to [...] Read more.
An energy management strategy for a series hybrid electric propulsion system designed for a fixed-wing vertical take-off and landing (VTOL) aircraft is presented in this paper. The proposed method combines an ideal operating line (IOL) and fuzzy logic. Fuzzy logic is used to dynamically and optimally allocate the output power of the generator and the battery pack according to the power requirement of the aircraft and the SOC of the battery pack. The IOL controller is used to optimize the internal combustion engine (ICE) operating point to improve the fuel economy of the system. The detailed aircraft model and energy system model are established. The flight process of a 100 kg scale VTOL aircraft under a typical mission profile is simulated. The simulation results show that running the ICE based on IOL can greatly improve its efficiency The introduction of fuzzy logic to optimize the power allocation of the generator and battery pack improves the overall efficiency of the system. The feasibility and effectiveness of the energy management strategy proposed in this paper are verified, and the design ideas and analysis methods are provided for the energy management of a hybrid electric aircraft. Full article
(This article belongs to the Special Issue Energy Efficiency of Small-Scale UAVs)
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29 pages, 9198 KiB  
Article
The Study of Electrical Energy Power Supply System for UAVs Based on the Energy Storage Technology
by Khac Lam Pham, Jan Leuchter, Radek Bystricky, Milos Andrle, Ngoc Nam Pham and Van Thuan Pham
Aerospace 2022, 9(9), 500; https://doi.org/10.3390/aerospace9090500 - 07 Sep 2022
Cited by 13 | Viewed by 9489
Abstract
Unmanned aerial vehicles (UAVs) are increasingly attracting investment and development attention from many countries all over the world due to their great advantages. However, one of the biggest challenges for researchers is the problem of supplying energy to UAVs to ensure they can [...] Read more.
Unmanned aerial vehicles (UAVs) are increasingly attracting investment and development attention from many countries all over the world due to their great advantages. However, one of the biggest challenges for researchers is the problem of supplying energy to UAVs to ensure they can operate for a longer time. Especially in the case of rotary wings, they consume more energy than other UAV types as the motors need to spend a lot of energy to operate in order to overcome the gravity of the earth. The article aims to research power supply, energy consumption on UAVs, and a method of taking advantage of external energy sources to provide power for the operation of UAVs and discuss UAVs’ structure, categories, and control. Two experiments were conducted separately to evaluate the energy consumption of UAVs and the energy conversion from external energy sources to electrical energy. A test bench was designed to evaluate and determine the maximum efficiency using regenerative braking mode. The measuring device was manufactured to measure the necessary parameters to calculate the energy consumption and performance of the system. Experimental numerical results show that energy conversion from external sources is one of methods that can help increase the flight time of the UAV. Full article
(This article belongs to the Special Issue Energy Efficiency of Small-Scale UAVs)
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21 pages, 1009 KiB  
Article
Energy-Efficient Trajectory Optimization for UAV-Enabled Cellular Communications Based on Physical-Layer Security
by Ziwei Yuan, Yanping Yang, Dong Wang and Xiaoping Ma
Aerospace 2022, 9(2), 50; https://doi.org/10.3390/aerospace9020050 - 20 Jan 2022
Cited by 3 | Viewed by 2472
Abstract
Low-altitude cellular-enabled Unmanned Aerial Vehicles (UAVs) provide potential supplementary platforms to assist air-to-ground cooperative communication. This paper investigates a joint safety information interaction scheme for a UAV-enabled network, which involves the complex constraints of three-dimensional trajectory planning, average energy efficiency optimization, and physical-layer [...] Read more.
Low-altitude cellular-enabled Unmanned Aerial Vehicles (UAVs) provide potential supplementary platforms to assist air-to-ground cooperative communication. This paper investigates a joint safety information interaction scheme for a UAV-enabled network, which involves the complex constraints of three-dimensional trajectory planning, average energy efficiency optimization, and physical-layer security. Specifically, by modeling the UAV and the Ground Station (GS) as the transmit sources, we define the secure Energy Efficiency (EE) as the ratio of the total secrecy rate to the energy consumption of the whole system. Then, to achieve secure and energy-efficient communication in eavesdropping scenarios, we formulated the optimization problem as maximizing both the uplink/downlink secure EE of the system, subject to the constraints of the UAV’s mobility and the allowable transmit power. For this highly coupled non-convex problem, a composite solution of joint fractional programming, alternate optimization, the bisection method, and the interior-point method is proposed to obtain the achievable EE. Simulation and performance analysis gave the conclusions that the joint optimization of trajectory and power allocation is capable of maximizing the information secure EE. Additionally, the secure EE increases with the increase of the average transmit power, which finally tends to be stable. Full article
(This article belongs to the Special Issue Energy Efficiency of Small-Scale UAVs)
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25 pages, 3141 KiB  
Article
Neuroevolutionary Control for Autonomous Soaring
by Eric J. Kim and Ruben E. Perez
Aerospace 2021, 8(9), 267; https://doi.org/10.3390/aerospace8090267 - 17 Sep 2021
Cited by 11 | Viewed by 2302
Abstract
The energy efficiency and flight endurance of small unmanned aerial vehicles (SUAVs) can be improved through the implementation of autonomous soaring strategies. Biologically inspired flight techniques such as dynamic and thermal soaring offer significant energy savings through the exploitation of naturally occurring wind [...] Read more.
The energy efficiency and flight endurance of small unmanned aerial vehicles (SUAVs) can be improved through the implementation of autonomous soaring strategies. Biologically inspired flight techniques such as dynamic and thermal soaring offer significant energy savings through the exploitation of naturally occurring wind phenomena for thrustless flight. Recent interest in the application of artificial intelligence algorithms for autonomous soaring has been motivated by the pursuit of instilling generalized behavior in control systems, centered around the use of neural networks. However, the topology of such networks is usually predetermined, restricting the search space of potential solutions, while often resulting in complex neural networks that can pose implementation challenges for the limited hardware onboard small-scale autonomous vehicles. In exploring a novel method of generating neurocontrollers, this paper presents a neural network-based soaring strategy to extend flight times and advance the potential operational capability of SUAVs. In this study, the Neuroevolution of Augmenting Topologies (NEAT) algorithm is used to train efficient and effective neurocontrollers that can control a simulated aircraft along sustained dynamic and thermal soaring trajectories. The proposed approach evolves interpretable neural networks in a way that preserves simplicity while maximizing performance without requiring extensive training datasets. As a result, the combined trajectory planning and aircraft control strategy is suitable for real-time implementation on SUAV platforms. Full article
(This article belongs to the Special Issue Energy Efficiency of Small-Scale UAVs)
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