Case Study: High-Precision Position Sensing Using Variable Reluctance Resolver Design

Overview

Magnet Methods has extensive experience in the design and optimisation of inductive and Hall-effect-based position sensors. This case study highlights our work on a 10-pole variable reluctance resolver (VRR), a rotary position sensor used in high-performance applications such as electric vehicle (EV) traction motors.

Project Scope

  • Sensor Types Supported:
    • LVDT (Linear Variable Differential Transformer)
    • RVDT (Rotary Variable Differential Transformer)
    • AC pick-offs
    • Multispeed resolvers
    • Brushless resolvers
    • Variable reluctance resolvers (VRRs)
  • Application: Shaft angle sensing for inverter-driven motors
  • Technology Used: 2D finite element modelling, flux linkage results used in spreadsheet based optimisation.
B modulus for 10-pole VRR

Design Highlights

Finite Element Modelling for Magnetic Flux Analysis

A 2D finite element model was developed to simulate the flux density distribution in the rotor and stator lamination stack of a 10-pole VRR. This model enabled:

  • Accurate mapping of magnetic field behaviour
  • Extraction of secondary coil flux linkage data
  • Visualisation of flux density for design validation

Optimisation of Secondary Coil Design

Using the flux linkage data from the FEM model, we performed spreadsheet-based calculations to:

  • Analyse signal characteristics
  • Minimise angular error
  • Optimise the distribution of secondary coil turns

This approach ensured high-resolution, low-error position sensing suitable for demanding motor control applications.

Engineering Considerations

  • Sensor Accuracy: Critical for precise motor control in EVs and industrial drives
  • Magnetic Design: Careful modelling of lamination geometry and pole configuration
  • Signal Processing: Use of analytical tools to refine coil design and reduce error

Conclusion

This project demonstrates Magnet Method’s ability to deliver high-precision rotary position sensors through a combination of electromagnetic simulation and analytical optimisation. Our approach ensures robust, accurate sensing solutions for advanced motor control systems.