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3D Platform for Coupling Coefficient Evaluation of an Inductive Power Transfer Systems.
Jure Domajnko1, Miro Milanovič1, Nataša Prosen1
1Faculty of Electrical Engineering and Computer Science, University of Maribor, 2000 Maribor, Slovenia.
A new 3D platform precisely measures the coupling coefficient in inductive wireless power transfer (IPT) systems. This tool aids in designing and evaluating IPT systems by mapping coil interactions in three dimensions.
Area of Science:
- Electrical Engineering
- Electromagnetics
- Wireless Power Transfer
Background:
- Inductive Wireless Power Transfer (IPT) systems require precise characterization of the coupling coefficient for optimal performance.
- Accurate measurement of mutual inductance between transmitter and receiver coils is crucial for system design and efficiency.
Purpose of the Study:
- To present a novel, computer-controlled 3D platform for evaluating the coupling coefficient in IPT systems.
- To enable precise spatial mapping of the coupling coefficient between transmitter and receiver coils.
Main Methods:
- Development of a custom 3D positioning mechanism integrated with a computer application.
- Implementation of an inductance measurement circuit to quantify mutual inductance at various spatial positions.
- Data acquisition and visualization on a connected computer for detailed analysis.
Main Results:
- The platform successfully measures mutual inductance and calculates the coupling coefficient in 3D space.
- Demonstrated ability to evaluate coupling coefficients at multiple spatial points, providing a comprehensive spatial map.
- Data collected can be used to extrapolate polynomial functions relating coupling coefficient to coil distance and misalignment.
Conclusions:
- The developed 3D platform is an effective tool for the design and evaluation phases of inductive wireless power transfer systems.
- This system facilitates a deeper understanding of coil coupling dynamics, enabling performance optimization.
- The ability to map and model coupling coefficients aids in predicting system behavior under varying spatial configurations.
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