Design of renewable energy based charging station for rotary wing UAVs

Year 2025, Volume: 9 Issue: 3, 240 - 258, 30.09.2025

Hakan Üçgün , Uğur Yüzgeç , Cüneyt Bayılmış

https://doi.org/10.30521/jes.1686759

Abstract

Unmanned Aerial Vehicles (UAVs) have emerged as remotely controlled aerial systems whose range of applications has expanded significantly in parallel with technological advancements. These vehicles, which do not carry human operators onboard, are widely utilized across various sectors due to their superior flight capabilities, low operational costs, and ease of development. However, their operational efficiency is often limited by short flight durations resulting from restricted battery capacities. To overcome this limitation, a renewable energy-supported charging station has been developed to enable rotary-wing UAVs to autonomously recharge during mission execution or standard flight operations. The proposed system integrates photovoltaic (PV) panels powered by solar energy as the primary energy source, alongside a battery storage unit. The conceptual design of the charging station is realized, simulation-based analyses are conducted, and hardware-testing procedures are implemented. The simulation studies include energy flow modeling between the PV panels, battery storage system, and the UAV battery. The autonomous charging of the battery and instantaneous charging status monitoring are performed via the charging pad in the developed system and the functionality is accomplished. According to the tests, the UAV has been charged in a balanced manner via the charging pad, regardless of the landing direction. The proposed system allows the autonomous charging of rotary wing UAV batteries without any human intervention and mission flight.

Keywords

Charging station , Photovoltaic panel , Renewable energy , Rotary wing , UAV

References

• [1] Çelebi Y, Aydın H. Multirotor unmanned aerial vehicle systems: an in-depth analysis of hardware, software, and communication systems. J Aviat. 2025;9(1):225-240. doi:10.30518/jav.1567696
• [2] Zhang J, Zhang L, Wu Y, Ma L, Yang F. An integrated modeling, verification, and code generation for uncrewed aerial systems: less cost and more efficiency. PeerJ Comput Sci. 2025;11:e2575. doi:10.7717/peerj-cs.2575
• [3] Alzubaidi AA. Systematic literature review for detecting intrusions in unmanned aerial vehicles using machine and deep learning. IEEE Access. 2025;13:58576-58599. doi:10.1109/ACCESS.2025.3552329
• [4] Lee C, Kim S, Chu BA. Survey: flight mechanism and mechanical structure of the UAV. Int J Precis Eng Manuf. 2021;22:719-743. doi:10.1007/s12541-021-00489-y
• [5] Al-Haddad LA, Łukaszewicz A, Majdi HS, Holovatyy A, Jaber AA, Al-Karkhi MI, et al. Energy consumption and efficiency degradation predictive analysis in unmanned aerial vehicle batteries using deep neural networks. Adv Sci Technol Res J. 2025;19(5):21-30. doi:10.12913/22998624/201346
• [6] Rai A, Peddinti PRT, Kim B, Han SS, Park SJ. Phenotypic trait monitoring of Victoria amazonica plants using unmanned aerial vehicles. J Indian Soc Remote Sens. 2025;53(5):1-19. doi:10.1007/s12524-025-02151-w
• [7] Rohan A, Rabah M, Talha M, Kim SH. Development of intelligent drone battery charging system based on wireless power transmission using hill climbing algorithm. Appl Syst Innov. 2018;1:44. doi:10.3390/asi1040044
• [8] Üçgün H, Yüzgeç U, Bayılmış C. A review on applications of rotary-wing unmanned aerial vehicle charging stations. Int J Adv Robot Syst. 2021;18(3):1-20. doi:10.1177/17298814211015863
• [9] Kokkinos S, Mourgelas C, Micha E, Chatzistavrakis E, Ioannis V. Design and implementation of drones charging station. In: Proceedings of the 27th Pan-Hellenic Conference on Progress in Computing and Informatics (PCI '23). New York, NY: Association for Computing Machinery; 2024. p.116-122. doi:10.1145/3635059.3635077
• [10] Lieret M, Wurmer F, Hofmann C, Franke J. An overhead docking and charging station for autonomous unmanned aircraft. In: 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE); 2021. p.1358-1363. doi:10.1109/CASE49439.2021.9551679
• [11] Al-Obaidi MR, Wan Hasan WZ, Mustafa MA, Azis N. Charging platform of chess-pad configuration for unmanned aerial vehicle (UAV). Appl Sci. 2020;10(23):8365. doi:10.3390/app10238365
• [12] Kim J, Jo H, Seo S, Lee B, Min H, Bien F. A multi-UAV charging station enabling free landing by grid pattern transmitter. In: 2025 IEEE Applied Power Electronics Conference and Exposition (APEC). Atlanta, GA, USA: IEEE; 2025. p.1629-1634. doi:10.1109/APEC48143.2025.10977481
• [13] Lv X, Li Y, Chen Z, Zhang W, Lin Z, Liu C, et al. A high misalignment tolerance SCC-WPT system with relay single capacitive coupler for UAV wireless charging applications. IEEE Trans Power Electron. 2025;40(8):10372-10377. doi:10.1109/TPEL.2025.3554676
• [14] Shaikh PW, Mouftah HT. Edge computing-aided dynamic wireless charging and trip planning of UAVs. J Sens Actuator Netw. 2025;14(1):8. doi:10.3390/jsan14010008
• [15] Song Y, Kim H, Byun J, Park K, Kim M, Lee SJ. Aerial dockable multirotor UAVs: design, control, and flight time extension through in-flight battery replacement. IEEE Access. 2025;13:96782-96799. doi:10.1109/ACCESS.2025.3574452
• [16] Chen J, Li W, Sha Y, et al. Autonomous battery-changing system for UAV’s lifelong flight. Biomim Intell Robot. 2023;3(2):1-10. doi:10.1016/j.birob.2023.100104
• [17] Guetta Y, Shapiro A. On-board physical battery replacement system and procedure for drones during flight. IEEE Robot Autom Lett. 2022;7(4):9755-9762. doi:10.1109/LRA.2022.3190077
• [18] Liau YS, Hong YWP, Sheu JP. Laser-powered UAV trajectory and charging optimization for sustainable data-gathering in the Internet of Things. IEEE Trans Mob Comput. 2025;24(5):4278-4295. doi:10.1109/TMC.2024.3523281
• [19] Luo C, Liu N, Hou Y, Hong Y, Chen Z, Li D. Trajectory optimization of laser-charged UAV to minimize the average age of information for wireless rechargeable sensor network. Theor Comput Sci. 2023;945:113680. doi:10.1016/j.tcs.2022.12.030
• [20] Ma X, Liu X, Ansari N. Green laser-powered UAV far-field wireless charging and data backhauling for a large-scale sensor network. IEEE Internet Things J. 2024;11(19):31932-31946. doi:10.1109/JIOT.2024.3422252
• [21] Nieuwoudt H, Welgemoed J, van Niekerk T, Phillips R. Automated charging and docking station for security UAVs. In: 2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT); Cape Town, South Africa; 2023. p.32-38. doi:10.1109/ICMIMT59138.2023.10200192
• [22] Moortgat-Pick A, Schwahn M, Adamczyk A, Duecker DA, Haddadin S. Autonomous UAV mission cycling: a mobile hub approach for precise landings and continuous operations in challenging environments. In: 2024 IEEE International Conference on Robotics and Automation (ICRA); Yokohama, Japan; 2024. p.8450-8456. doi:10.1109/ICRA57147.2024.10611292
• [23] Li J, Dou Z, Liu F. Design and implementation of autonomous wireless charging shelter for UAV group. In: 2023 3rd International Conference on Energy Engineering and Power Systems (EEPS); Dali, China; 2023. p.1091-1095. doi:10.1109/EEPS58791.2023.10256955
• [24] Ağçal A, Doğan TH. A novel folding wireless charging station design for drones. Drones. 2024;8(7):289. doi:10.3390/drones8070289
• [25] Grlj CG, Krznar N, Pranjić M. A decade of UAV docking stations: a brief overview of mobile and fixed landing platforms. Drones. 2022;6(1):17. doi:10.3390/drones6010017
• [26] Li Y, Sugihara J, Nishio T, Zhao M. Cooperative navigation system of AGV and UAV with autonomous and precise landing. In: 2024 IEEE International Conference on Mechatronics and Automation (ICMA); 2024. p.1477-1483. doi:10.1109/ICMA61710.2024.10633166
• [27] Messaoudi K, Baz A, Oubbati OS, Rachedi A, Bendouma T, Atiquzzaman M. UGV charging stations for UAV-assisted AoI-aware data collection. IEEE Trans Cogn Commun Netw. 2024;10(6):2325-2343. doi:10.1109/TCCN.2024.3394859
• [28] Sarvi M, Azadian A. A comprehensive review and classified comparison of MPPT algorithms in PV systems. Energy Syst. 2022;13:281-320. doi:10.1007/s12667-021-00427-x
• [29] Çakmak F, Aydoğmuş Z, Tür MR. Analyses of PO-based fuzzy logic-controlled MPPT and incremental conductance MPPT algorithms in PV systems. Energies. 2025;18(2):233. doi:10.3390/en18020233
• [30] Carkhuff BG, Demirev PA, Srinivasa R. Impedance-based battery management system for safety monitoring of lithium-ion batteries. IEEE Trans Ind Electron. 2018;65(8):6497-6504. doi:10.1109/TIE.2017.2786199