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Author Background

1st Author

MSc in Mechatronics Engineering with 5+ industrial Experience in aviation engineering

2nd Author

Gihad Ibrahim received a first-class B.Eng. (Hons) degree in Mechatronics Engineering from the School of Engineering, University of Wolverhampton, UK in 2008 and a Ph.D. from the Department of Engineering, University of Leicester, UK in 2015. He is an Assistant Professor in Engineering with an interest and experience in management and marketing within the education sector. Dr Ibrahim’s research efforts aim towards the multiphysics modelling of complex biological systems. The teaching experience of Dr Ibrahim focuses on the design, simulation, and analysis of mechatronic systems. He also teaches modules related to manufacturing processes, CAD/CAM, and robotics. Dr Ibrahim has successfully implemented educational projects related to E-learning and online presence in many institutions in developing countries during the COVID-19 pandemic He is inbound marketing and sales certified. He also has professional certificates in project management and marketing from Google and other well-established institutions. He is interested in developing novel management and marketing strategies for educational institutions. He also has good experience in establishing successful academic collaborations and in the development of joint programs. Dr Ibrahim is a full member of the Institute of Physics and Engineering in Medicine (IPEM) and an associate member of the Institution of Mechanical Engineers (IMechE). He is a quick learner and a self-motivated researcher. He has demonstrated the ability to solve a variety of analytical, technical, and practical problems using creative and innovative approaches.

Abstract

This paper proposes a computational framework to optimize the ambient power harvesting from an unmanned air vehicle wing by means of piezoelectricity. First, the wing shape and material are selected based on specific design factors. The wing is then subjected to a vibrational analysis in order to predict the first torsional frequency required to calculate an optimum charging speed. The harvester module is then selected so that the vibration frequency of the charging speed fails within the resonance frequency of the harvester. A finite element modeling is conducted to predict the harvester output voltage during the chagrining speed. Finally, a power management circuit is designed to boost the harvester output voltage to 5V. The proposed framework was validated experimentally using the car-top rig method (error 2.18%). Twenty minutes of flight time were enough to recharge a 600mAh lithium-ion battery used to energize a 5V servomotor that controls the wing flap.

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