An Effective Method to Model and Simulate the Behavior of Inductive Angle Encoders

Area of Science:

• Electrical Engineering
• Electromagnetics
• Sensor Technology

Background:

• Inductive angle and position sensors often rely on coupled coils, modulating position information onto induced voltage.
• Calculating sensor performance involves complex eddy current physics, typically requiring computationally intensive 3D finite-element (FE) simulations.
• Existing simulation methods present significant time and resource limitations for design optimization.

Purpose of the Study:

• To develop a novel, computationally efficient method for simulating inductive angle sensors.
• To reduce the simulation effort required for characterizing sensor performance across various geometric parameters.
• To create predictive regression models that can replace or supplement traditional FE simulations.

Main Methods:

• Employed D-optimal designs, a technique from statistical design of experiments.
• Combined D-optimal designs with a numerical implementation of Faraday's law to calculate induced voltages from magnetic field data.
• Utilized shifting integration boundaries to derive sensor signals for multiple angles from a single simulation.

Main Results:

• Achieved significant reduction in simulation time for a full period of sensor operation.
• Developed regression models capable of predicting key sensor parameters, including Tx-coil inductance and induced Rx-voltage amplitude.
• Enabled accurate prediction of angular error as a function of geometric design parameters.

Conclusions:

• The presented method offers a computationally efficient alternative to traditional FE simulations for inductive angle sensors.
• The developed regression models provide a powerful tool for rapid design exploration and optimization.
• This approach facilitates faster development cycles and improved performance prediction for inductive sensing technologies.