Self-Calibrating Position Measurements: Applied to Imperfect Hall Sensors

Fuente: arXiv
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Main Authors: van Meer, Max, van Noije, Marijn, Tiels, Koen, Evers, Enzo, Blanken, Lennart, Witvoet, Gert, Oomen, Tom
Format: Preprint
Published: 2025
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author van Meer, Max
van Noije, Marijn
Tiels, Koen
Evers, Enzo
Blanken, Lennart
Witvoet, Gert
Oomen, Tom
author_facet van Meer, Max
van Noije, Marijn
Tiels, Koen
Evers, Enzo
Blanken, Lennart
Witvoet, Gert
Oomen, Tom
contents Linear Hall sensors are a cost-effective alternative to optical encoders for measuring the rotor positions of actuators, with the main challenge being that they exhibit position-dependent inaccuracies resulting from manufacturing tolerances. This paper develops a data-driven calibration procedure for linear analog Hall sensors that enables accurate online estimates of the rotor angle without requiring expensive external encoders. The approach combines closed-loop data collection with nonlinear identification to obtain an accurate model of the sensor inaccuracies, which is subsequently used for online compensation. Simulation results show that when the flux density model structure is known, measurement errors are reduced to the sensor noise floor, and experiments on an industrial setup demonstrate a factor of 2.6 reduction in the root-mean-square measurement error. These results confirm that Hall sensor inaccuracies can be calibrated even when no external encoder is available, improving their practical applicability.
format Preprint
id arxiv_https___arxiv_org_abs_2505_04245
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Self-Calibrating Position Measurements: Applied to Imperfect Hall Sensors
van Meer, Max
van Noije, Marijn
Tiels, Koen
Evers, Enzo
Blanken, Lennart
Witvoet, Gert
Oomen, Tom
Systems and Control
Linear Hall sensors are a cost-effective alternative to optical encoders for measuring the rotor positions of actuators, with the main challenge being that they exhibit position-dependent inaccuracies resulting from manufacturing tolerances. This paper develops a data-driven calibration procedure for linear analog Hall sensors that enables accurate online estimates of the rotor angle without requiring expensive external encoders. The approach combines closed-loop data collection with nonlinear identification to obtain an accurate model of the sensor inaccuracies, which is subsequently used for online compensation. Simulation results show that when the flux density model structure is known, measurement errors are reduced to the sensor noise floor, and experiments on an industrial setup demonstrate a factor of 2.6 reduction in the root-mean-square measurement error. These results confirm that Hall sensor inaccuracies can be calibrated even when no external encoder is available, improving their practical applicability.
title Self-Calibrating Position Measurements: Applied to Imperfect Hall Sensors
topic Systems and Control
url https://arxiv.org/abs/2505.04245