A wireless charging method with lightweight pick-up structure for UAVs-Reference-Cited by-同舟云学术

A wireless charging method with lightweight pick-up structure for UAVs

Published:2021-04-07 Issue:6 Volume:103 Page:2847-2854
ISSN:0948-7921
Container-title:Electrical Engineering
language:en
Short-container-title:Electr Eng

Author:

Zhai Xuefeng,Wang Hongxing,Li Jun,Huang Zheng,Gao Ruozhong^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Electrical and Electronic Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00202-021-01267-9.pdf

Reference19 articles.

1. Junaid AB, Lee Y, Kim Y (2016) Design and implementation of autonomous wireless charging station for rotary-wing UAVs. Aerosp Sci Technol 54:253–266

2. Kumar S, Jayp R (2017) Wireless power transfer for unmanned aerial vehicle (UAV) charging. Int Res J Eng Technol 4:1939–1946

3. Ke D, Liu C, Jiang C (2017) Design of an effective wireless air charging system for electric unmanned aerial vehicles. In: Proceedings of 43rd annual conference of the IEEE Industrial. Beijing, pp 6949–6954

4. Campi T, Cruciani S, Maradei F (2019) Innovative design of drone landing gear used as a receiving coil in wireless charging application. Energies 18:1–20

5. Covic GA, Boys JT (2013) Inductive power transfer. Proc IEEE 101:1276–1289

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A survey of energy efficient methods for UAV communication;Vehicular Communications;2023-06

2. Optimization of Efficiency and Receiver-Coil Mass in an Autonomous 700-W S-S IPT System for UAV Applications;2023 IEEE Applied Power Electronics Conference and Exposition (APEC);2023-03-19

3. In-Flight Wireless Charging: A Promising Application-Oriented Charging Technique for Drones;IEEE Industrial Electronics Magazine;2023

4. Critical Review of Recent Development of Wireless Power Transfer Technology for Unmanned Aerial Vehicles;IEEE Access;2023

5. Optimization for Master-UAV-Powered Auxiliary-Aerial-IRS-Assisted IoT Networks: An Option-Based Multi-Agent Hierarchical Deep Reinforcement Learning Approach;IEEE Internet of Things Journal;2022-11-15