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Related Experiment Video

Updated: Sep 13, 2025

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Deep Neural Network-Based Design of Planar Coils for Proximity Sensing Applications.

Abderraouf Lalla1, Paolo Di Barba1, Sławomir Hausman2

  • 1Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Via Ferrata 5, 27100 Pavia, Italy.

Sensors (Basel, Switzerland)
|July 30, 2025
PubMed
Summary

This study introduces a deep learning method to design planar coils for specific magnetic fields. The AI discovers efficient coil geometries, simplifying manufacturing and enhancing performance in various applications.

Keywords:
CNN-based coil geometry modelsdeep learningmagnetic fieldplanar coils

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Area of Science:

  • Electrical Engineering
  • Computational Electromagnetics
  • Artificial Intelligence

Background:

  • Designing planar coils with specific magnetic field characteristics is crucial for applications like wireless power transfer and sensors.
  • Traditional coil design methods can be complex and time-consuming, often requiring iterative optimization.
  • The need for efficient and accurate methods to generate custom coil geometries is increasing.

Purpose of the Study:

  • To develop a deep learning procedure for identifying planar coil geometries based on desired magnetic field maps.
  • To demonstrate the capability of this approach in discovering accurate and efficient coil designs.
  • To provide a flexible tool for advanced planar coil design.

Main Methods:

  • A deep learning procedure was developed to predict planar coil geometry.
  • The procedure takes a desired magnetic field map as input.
  • The output is a coil design that generates the target magnetic field.

Main Results:

  • The deep learning approach successfully identified suitable planar coil geometries.
  • The generated coils produced magnetic fields with high accuracy and efficiency, closely matching target fields.
  • The method enables the creation of simpler coil structures with improved performance.

Conclusions:

  • Deep learning offers a powerful and flexible tool for advanced planar coil design.
  • This method can significantly aid in the development of inductive proximity sensors, wireless power transfer systems, and electromagnetic compatibility solutions.
  • The approach facilitates the manufacturing of coils with enhanced performance and simpler structures.