Development of intelligent drone battery charging system based on wireless power transmission using hill climbing algorithm.

Rohan, Ali; Rabah, Mohammed; Talha, Muhammad; Kim, Sung-Ho

Abstract

In this work, an advanced drone battery charging system is developed. The system is composed of a drone charging station with multiple power transmitters and a receiver to charge the battery of a drone. A resonance inductive coupling-based wireless power transmission technique is used. With limits of wireless power transmission in inductive coupling, it is necessary that the coupling between a transmitter and receiver be strong for efficient power transmission; however, for a drone, it is normally hard to land it properly on a charging station or a charging device to get maximum coupling for efficient wireless power transmission. Normally, some physical sensors such as ultrasonic sensors and infrared sensors are used to align the transmitter and receiver for proper coupling and wireless power transmission; however, in this system, a novel method based on the hill climbing algorithm is proposed to control the coupling between the transmitter and a receiver without using any physical sensor. The feasibility of the proposed algorithm was checked using MATLAB. A practical test bench was developed for the system and several experiments were conducted under different scenarios. The system is fully automatic and gives 98.8% accuracy (achieved under different test scenarios) for mitigating the poor landing effect. Also, the efficiency η of 85% is achieved for wireless power transmission. The test results show that the proposed drone battery charging system is efficient enough to mitigate the coupling effect caused by the poor landing of the drone, with the possibility to land freely on the charging station without the worry of power transmission loss.

Citation

ROHAN, A., RABAH, M., TALHA, M. and KIM, S.-H. 2018. Development of intelligent drone battery charging system based on wireless power transmission using hill climbing algorithm. Applied system innovation [online], 1(4), article 44. Available from: https://doi.org/10.3390/asi1040044

• Journal Article Type: Article
• Acceptance Date: Nov 5, 2018
• Online Publication Date: Nov 7, 2018
• Publication Date: Dec 31, 2018
• Deposit Date: Jun 13, 2023
• Publicly Available Date: Jun 13, 2023
• Journal: Applied system innovation
• Electronic ISSN: 2571-5577
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 1
• Issue: 4
• Article Number: 44
• DOI: https://doi.org/10.3390/asi1040044
• Keywords: Wireless power transfer; Unmanned aerial vehicle; Automatic charging station; Drone station; hill climbing
• Public URL: https://rgu-repository.worktribe.com/output/1982517