Acoustic Noise Reduction in Resolver-Based PMSM Servo Drives Using NLMS Adaptive Filtering

Servo drives that utilize resolvers for angular feedback typically exhibit higher noise levels than those equipped with optical encoders, particularly when the servo drive system operates with higher control bandwidths. In such cases, resolver noise can introduce additional acoustic noise. This paper presents some of the main causes of noise in servo drive systems associated with resolvers, proposes a novel noise suppression method based on Normalized Least-Mean-Square (NLMS) adaptive filters, and compares it with conventional notch filter-based noise reduction techniques. Simulations and experiments demonstrate that this method can effectively reduce audible noise in the servo system without compromising the dynamic performance of the current control loops.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.23919/icems60997.2024.10921306
Primary Topic
Iterative Learning Control Systems
Type
article
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article

Acoustic Noise Reduction in Resolver-Based PMSM Servo Drives Using NLMS Adaptive Filtering

Chaohui Liang, Duhuang Su, Tao Li
Iterative Learning Control Systems
article

Acoustic Noise Reduction in Resolver-Based PMSM Servo Drives Using NLMS Adaptive Filtering

Chaohui Liang, Duhuang Su, Tao Li
article en

Abstract

Servo drives that utilize resolvers for angular feedback typically exhibit higher noise levels than those equipped with optical encoders, particularly when the servo drive system operates with higher control bandwidths. In such cases, resolver noise can introduce additional acoustic noise. This paper presents some of the main causes of noise in servo drive systems associated with resolvers, proposes a novel noise suppression method based on Normalized Least-Mean-Square (NLMS) adaptive filters, and compares it with conventional notch filter-based noise reduction techniques. Simulations and experiments demonstrate that this method can effectively reduce audible noise in the servo system without compromising the dynamic performance of the current control loops.

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