Design and application of optimum toroidal shaped electromagnetic energy harvesters for unmanned aerial vehicles
This study presents the design and implementation of electromagnetic energy harvesters for the purpose of charging unmanned aerial vehicles (UAVs) battery. In the study, the designed harvesters are analyzed through finite element method (FEM) simulations. In the FEM analysis, common and self‐inducta...
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Published in: | International journal of numerical modelling Vol. 37; no. 3 |
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Main Authors: | , |
Format: | Journal Article |
Language: | English |
Published: |
Chichester, UK
John Wiley & Sons, Inc
01-05-2024
Wiley Subscription Services, Inc |
Subjects: | |
Online Access: | Get full text |
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Summary: | This study presents the design and implementation of electromagnetic energy harvesters for the purpose of charging unmanned aerial vehicles (UAVs) battery. In the study, the designed harvesters are analyzed through finite element method (FEM) simulations. In the FEM analysis, common and self‐inductance values, as well as magnetic flux density values of the harvesters, are calculated at specific current values. Inductance values are also theoretically calculated for comparison. Subsequently, an experimental setup is established to test the designed harvesters. After winding the core, the induced voltage and the power transferred to the load by the harvesters are measured. Curve fitting is performed after the measurements with different load resistances to find the maximum power transferred to the load. Through curve fitting, the maximum power obtained at each current value and at which load resistance this power is harvested are determined. Considering the intention of using the designed cores to charge UAVs and the importance of weight in UAV flight, the weights of each core, both without winding and after winding, are measured, and their costs are calculated. Taking all these criteria into account, the performance of the harvesters is demonstrated, and those among the used cores that are the most suitable for UAVs are identified in the study. |
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ISSN: | 0894-3370 1099-1204 |
DOI: | 10.1002/jnm.3260 |