Orientation measurement based on magnetic inductance by the extended distributed multi-pole model

Area of Science:

• Electromagnetism and Magnetic Field Theory
• Computational Physics and Engineering

Background:

• Mutual inductance calculations are crucial for position/orientation tracking but face challenges in real-time applications due to computational demands.
• Existing numerical methods for magnetic field analysis require heavy computation and are limited by geometric modeling and meshing complexities.
• Analytical methods offer speed but struggle with complex geometries and boundary conditions.

Purpose of the Study:

• To develop a novel, fast-computing magnetic field model for accurate magnetic inductance calculation.
• To extend the existing Distributed Multi-pole (DMP) model for characterizing time-varying magnetic fields.
• To compute mutual inductance between coils at arbitrary positions and orientations.

Main Methods:

• Development of the extended Distributed Multi-pole (eDMP) model, building upon the static DMP model.
• Application of the eDMP model to characterize time-varying magnetic fields.
• Computation of mutual inductance between coils using the eDMP model for various configurations.

Main Results:

• The eDMP model demonstrates effectiveness in computing mutual inductance between coils.
• Simulations and experimental results validate the accuracy and computational efficiency of the eDMP model.
• The proposed method shows good performance in accuracy compared to previously published data.

Conclusions:

• The extended distributed multi-pole (eDMP) model provides an accurate and computationally efficient solution for magnetic inductance calculations.
• This novel method addresses the limitations of existing numerical and analytical approaches for magnetic field analysis.
• The eDMP model is effective for real-time applications requiring robust magnetic field modeling, such as position/orientation tracking systems.