Skip to main content

Research Repository

Advanced Search

Analysis and design of position and velocity estimation scheme for PM servo motor drive with binary Hall sensors

Ni, Oinan; Yang, Ming; Odhano, Shafia Ahamed; Zanchetta, Pericle; Liu, Xiaosheng; Xu, Dianguo

Authors

Oinan Ni

Ming Yang

Shafia Ahamed Odhano

Xiaosheng Liu

Dianguo Xu



Abstract

With the increasing demand of low-cost, high-efficiency, high performance for AC motor drive system, the permanent-magnet synchronous motor (PMSM) with binary Hall sensors begins to be adopted in many fields. Compared with sensorless control, the usage of binary Hall sensors is a guarantee for the drive to achieve moderate control performance, and it is in smaller volume and more cost-effective compared with other types of position sensors. In this paper, a solution is provided to realize fully-closed loop control with low-resolution position sensors, by treating the position and speed estimators as separate systems. Results reveal that the model-based methods can take advantage of model information and model-free methods can smoothly process the quantized Hall position signal. Extensive experiment results are provided demonstrating the position control performance and basic servo performance for a PMSM drive using 3 bit-per-pole-pair sensing system.

Citation

Ni, O., Yang, M., Odhano, S. A., Zanchetta, P., Liu, X., & Xu, D. (2018). Analysis and design of position and velocity estimation scheme for PM servo motor drive with binary Hall sensors. In 2018 IEEE Energy Conversion Congress and Exposition (ECCE). https://doi.org/10.1109/ECCE.2018.8558123

Conference Name 2018 IEEE Energy Conversion Congress and Exposition (ECCE)
Conference Location Portland, OR
Start Date Sep 23, 2018
End Date Sep 27, 2018
Acceptance Date Apr 12, 2018
Online Publication Date Dec 6, 2018
Publication Date Sep 23, 2018
Deposit Date Feb 18, 2019
Publicly Available Date Mar 29, 2024
Publisher Institute of Electrical and Electronics Engineers
Book Title 2018 IEEE Energy Conversion Congress and Exposition (ECCE)
ISBN 9781479973132
DOI https://doi.org/10.1109/ECCE.2018.8558123
Public URL https://nottingham-repository.worktribe.com/output/1563391
Publisher URL https://ieeexplore.ieee.org/document/8558123

Files




You might also like



Downloadable Citations