Design and optimisation of linear variable differential transformers and voice coil actuators using finite element analysis: a methodical approach to enhance sensor response and actuation force

TL;DR

This paper presents a systematic finite element analysis-based methodology for designing optimized LVDT sensors and voice coil actuators, improving performance for high-precision applications like gravitational wave detection.

Contribution

It introduces a novel, structured design process for LVDT and VC systems, addressing performance trade-offs and validating results with experiments.

Findings

Optimized coil and gap parameters enhance sensor response.

Design trade-offs improve actuation force while managing heat dissipation.

Validated simulation results with experimental measurements.

Abstract

This study introduces a systematic and optimised methodology for designing Linear Variable Differential Transformer (LVDT) sensors and Voice Coil (VC) actuators, tailored for high-precision applications such as gravitational wave detectors and particle accelerators. Unlike prior studies, which focus primarily on industrial-grade LVDT design frameworks or isolated parameter studies, this work addresses the specific challenges of achieving both enhanced sensor response and actuation force within strict geometric and thermal constraints. Using a custom-developed simulation pipeline based on Finite Element Method Magnetics (FEMM), we evaluate the effects of key parameters such as coil dimensions, radial gaps, and coil wire diameter on performance metrics such as response and linearity. The novelty of this work lies in its systematic exploration of design trade-offs, such as maximising performance while minimising heat dissipation, and its applicability to high-precision environments. In this work, we focus in particular on the combination of the LVDT and VC functionalities in one unified sensor-and-actuator system designed for gravitational wave detectors. In addition, the methodology and simulation results are validated with experimental measurements of an optimised design. This work represents a significant advance over existing methodologies by offering a structured, scalable design process.