Simulation and Control Design of a Midrange WPT Charging System for In-Flight Drones

Oussama Allama, Mohamed Hadi Habaebi (), Sheroz Khan, Md. Rafiqul Islam and Abdullah Alghaihab
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Oussama Allama: IoT & Wireless Communication Protocols Laboratory, Department of Electrical Computer Engineering, International Islamic University, Kuala Lumpur 53100, Malaysia
Mohamed Hadi Habaebi: IoT & Wireless Communication Protocols Laboratory, Department of Electrical Computer Engineering, International Islamic University, Kuala Lumpur 53100, Malaysia
Sheroz Khan: Department of Electrical and Renewable Energy Engineering, Unaizah Colleges of Engineering, Unaizah 56453, Saudi Arabia
Md. Rafiqul Islam: IoT & Wireless Communication Protocols Laboratory, Department of Electrical Computer Engineering, International Islamic University, Kuala Lumpur 53100, Malaysia
Abdullah Alghaihab: Department of Electrical Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia

Energies, 2023, vol. 16, issue 15, 1-19

Abstract: Drones, or unmanned aerial vehicles (UAVs), have emerged as an indispensable tool across numerous industries due to their remarkable versatility, efficiency, and capabilities. Notwithstanding all these traits, drones are still limited by battery life. In this paper, we propose a genuine in-flight charging method without landing. The charging system consists of three orthogonal coils, among which the receiving coil is connected to the drone. The development of the model for wireless dynamic charging systems is achieved by integrating the receiver trajectory and velocity in the model. Furthermore, the model is significantly enhanced by introducing the concept of the positioning mutual coupling function for the receiver trajectory; thus, it is possible to simulate a genuine continuous trajectory for UAVs and link it to the systems’ total input power consumption. The developed control algorithm can direct the magnetic field resultant to track the exact trajectory of the drone. The real-time simulation of the multiparameter discrete extremum-seeking control (ESC) algorithm on the (DSP) F28379D hardware shows that the input power is maximized up to 12 W in a response time of 2 ms for a drone-hovering velocity of 8 m/s without any feedback.

Keywords: wireless power transfer; UAVs; in-flight charging; magnetic tracking; multiparameter ESC; dynamic charging; controlled omnidirectional WPT (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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