A New Battery Selection System and Charging Control of a Movable Solar-Powered Charging Station for Endless Flying Killing Drones

Essam Ali, Mohamed Fanni and Abdelfatah M. Mohamed
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Essam Ali: Mechatronics and Robotics Engineering Department, Egypt-Japan University of Science and Technology, Alexandria 21934, Egypt
Mohamed Fanni: Mechatronics and Robotics Engineering Department, Egypt-Japan University of Science and Technology, Alexandria 21934, Egypt
Abdelfatah M. Mohamed: Mechatronics and Robotics Engineering Department, Egypt-Japan University of Science and Technology, Alexandria 21934, Egypt

Sustainability, 2022, vol. 14, issue 4, 1-20

Abstract: This paper provides a design, a charging control, and energy management of a movable Photo Voltaic (PV) charging station with an Automatic Battery Replacement (ABR) system to enable drones for ongoing missions. The paper represents the first stage of a three-staged project titled Fall Armyworm (FAW) insect killer. The other two stages involve the flight control of drones and detecting and killing FAW insects. Without chemical methods, the project aims to eliminate harmful FAW insects that are rapidly spreading in Africa and Asia. The power source is a hybrid PV system with energy storage devices (batteries and supercapacitors). The maximum power from PV panels is tracked using three different online methods (PSO, IC, and P&O), and the best method with the highest accuracy is selected. The experimental and simulation results approved that PSO is the recommended method used in this project among the studied methods because of its high target reach (about 97%) and low steady-state oscillation (maximum 2.15%). An intelligent energy management system is investigated and designed to efficiently utilize solar power with a constant-current constant-voltage charger for LiPo batteries. A new Battery Selection System (BSS) is designed and verified to efficiently utilize the harvested energy and increase the mission time. The BSS targets to manage the selection of the appropriate battery to charge and control its charging rate. The system performance is tested using MATLAB software. Then, an experimental setup for the system is built to validate simulation results. The results of simulations and experiments proved the reliability of BSS in different operating cases with an efficiency higher than 97%.

Keywords: automatic battery replacement; CCCV charging; battery selection system; drone; PV; insect killer; PSO; IC; P&O (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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