TY - GEN
T1 - On-line Parameter Identification of Permanent Magnet Synchronous Motor based on Extended Kalman Filter
AU - Hu, Tianzi
AU - Liu, Jiaxi
AU - Cao, Jiwei
AU - Li, Liyi
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Accurate motor parameters are the basic requirements for realizing high-performance control technology of permanent magnet synchronous motors (PMSM). To maintain high performance in different operation mode, it is necessary to adjust the control with different conditions. However, on-line parameter identification is hardly to have better precision. A parameter identification method for surface-mounted permanent magnet synchronous motor (SPMSM) based on extended Kalman filter is proposed to solve this problem. By using this scheme, the accuracy and speed of parameter identification can be effectively improved. In this paper, the stator resistance, rotor flux, inductance, moment of inertia and load torque of SPMSM are identified, and the anti-interference of the algorithm is also analyzed. Simulation results verify the correctness and effectiveness of the method, and show that the parameter identification results can converge quickly and the error is limited within a small range.
AB - Accurate motor parameters are the basic requirements for realizing high-performance control technology of permanent magnet synchronous motors (PMSM). To maintain high performance in different operation mode, it is necessary to adjust the control with different conditions. However, on-line parameter identification is hardly to have better precision. A parameter identification method for surface-mounted permanent magnet synchronous motor (SPMSM) based on extended Kalman filter is proposed to solve this problem. By using this scheme, the accuracy and speed of parameter identification can be effectively improved. In this paper, the stator resistance, rotor flux, inductance, moment of inertia and load torque of SPMSM are identified, and the anti-interference of the algorithm is also analyzed. Simulation results verify the correctness and effectiveness of the method, and show that the parameter identification results can converge quickly and the error is limited within a small range.
KW - extended Kalman filter
KW - parameter identification
KW - permanent magnet synchronous motor
UR - https://www.scopus.com/pages/publications/85146353653
U2 - 10.1109/ICEMS56177.2022.9983414
DO - 10.1109/ICEMS56177.2022.9983414
M3 - 会议稿件
AN - SCOPUS:85146353653
T3 - 2022 International Conference on Electrical Machines and Systems, ICEMS 2022
BT - 2022 International Conference on Electrical Machines and Systems, ICEMS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th International Conference on Electrical Machines and Systems, ICEMS 2022
Y2 - 29 November 2022 through 2 December 2022
ER -