Self-Calibrating Position Measurements
Applied to Imperfect Hall Sensors
Max Van Meer (Eindhoven University of Technology)
Marijn Van Noije (Eindhoven University of Technology)
Koen Tiels (Eindhoven University of Technology)
Enzo Evers (Sioux Technologies)
Lennart Blanken (Eindhoven University of Technology, Sioux Technologies)
Gert Witvoet (Eindhoven University of Technology, TNO)
Tom Oomen (TU Delft - Team Jan-Willem van Wingerden, Eindhoven University of Technology)
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Abstract
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.
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