Analytical approximations for magnetic coupling coefficients between adjacent coils

TL;DR

This paper introduces a simple geometric model to accurately approximate magnetic coupling coefficients between adjacent coils, validated against finite element analysis, with potential applications in coil separation estimation.

Contribution

The paper presents a novel 2D geometric approximation method for predicting magnetic coupling between coils, validated against FE simulations with high accuracy.

Findings

Excellent agreement with FE results (residual <0.5%)

Predicts coupling trends with separation and displacement accurately

Applicable for automated coil separation and surface curvature estimation

Abstract

This paper presents a simple yet novel two-dimensional modelling approach for approximating the coupling coefficient between neighbouring inductors as a function of co-planar separation and relative angular displacement. The approach employs simple geometric arguments to predict the effective magnetic flux between inductors. Two extreme coil geometry regimes are considered; planar coils (i.e. on printed circuit board), and solenoid coils, each with asymmetric ferrite cores about the central magnetic plane of the inductor. The proposed geometric approximation is used to predict the coupling coefficient between sensors as a function of separation distance and angular displacement and the results are validated against two-dimensional finite element modelling results. The analytical approximations show excellent agreement with the FE analysis, predicting comparable trends with changing separation and angular displacement, enabling best fitting to 2D FE and 3D numerical data with a residual standard deviation of less than 0.5\% for the planar coil approximation. The work demonstrates the validity of the analytical approximation for predicting coupling behaviour between neighbouring coils. This has practical uses for the automated estimation of the physical separation between coils, or the curvature of surfaces they are rested or adhered to.