Design of sensorless system for PMSM based on UKF

Xiaogang Wang; Tao Li; Yan Lv; Yuanliang Zhang

doi:10.1117/12.2681069

23 May 2023 Design of sensorless system for PMSM based on UKF

Xiaogang Wang, Tao Li, Yan Lv, Yuanliang Zhang

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 126450R (2023) https://doi.org/10.1117/12.2681069
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

Aiming at the defect that the parameter variation affects the performance of the non-inductive observer during the long running time, the UKF is introduced into the design of sensor-less control system of permanent magnet synchronous motor. In this paper, the resistance and inductance are used as the expanded dimension state variables for state estimation to ensure the stable operation of the non-inductive observation algorithm. On this basis, the design scheme of PMSM control system is given, and the experiment is carried out to compare the improved non-inductive observation algorithm with the traditional non-inductive observation algorithm in the electrical angle estimation, and the experiment proves the excellent performance of the system for motor speed control.

Citation Download Citation

Xiaogang Wang, Tao Li, Yan Lv, and Yuanliang Zhang "Design of sensorless system for PMSM based on UKF", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 126450R (23 May 2023); https://doi.org/10.1117/12.2681069

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available