TY - JOUR
T1 - Online Parameter Identification for Model-Based Sensorless Control of Interior Permanent Magnet Synchronous Machine
AU - Rafaq, Muhammad Saad
AU - Mwasilu, Francis
AU - Kim, Jinuk
AU - Choi, Han Ho
AU - Jung, Jin Woo
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/6
Y1 - 2017/6
N2 - This paper proposes an online identification method that can accurately estimate the stator resistance and dq-axis stator inductances for the effective model-based sensorless control of interior permanent magnet synchronous motors (IPMSMs). The proposed affine projection algorithms are uniquely designed in the estimated rotating γ-δ frame to precisely identify the parameters mentioned above. The two time-scale approaches are employed in the affine projection algorithms to estimate the three electrical parameters. Despite the electrical parameter variations due to the temperature change and magnetic saturation during operation, the rich enough data are provided to the affine projection algorithms in the discrete-time domain to accurately retrieve the updated parameters. These correctly estimated parameters are adapted to the extended back electromotive force observer for the sensorless control of IPMSM drives. Hence, the adaptation of online updated parameters makes the observer stable and robust to parameter variations as compared to the conventional observer without updated parameters. The MATLAB/Simulink-based simulation results and experimental results via a prototype IPMSM test-bed having TMS320F28335 DSP are given to verify the accurate convergence of the estimated parameters, which results into a stable sensorless control system under various operating conditions.
AB - This paper proposes an online identification method that can accurately estimate the stator resistance and dq-axis stator inductances for the effective model-based sensorless control of interior permanent magnet synchronous motors (IPMSMs). The proposed affine projection algorithms are uniquely designed in the estimated rotating γ-δ frame to precisely identify the parameters mentioned above. The two time-scale approaches are employed in the affine projection algorithms to estimate the three electrical parameters. Despite the electrical parameter variations due to the temperature change and magnetic saturation during operation, the rich enough data are provided to the affine projection algorithms in the discrete-time domain to accurately retrieve the updated parameters. These correctly estimated parameters are adapted to the extended back electromotive force observer for the sensorless control of IPMSM drives. Hence, the adaptation of online updated parameters makes the observer stable and robust to parameter variations as compared to the conventional observer without updated parameters. The MATLAB/Simulink-based simulation results and experimental results via a prototype IPMSM test-bed having TMS320F28335 DSP are given to verify the accurate convergence of the estimated parameters, which results into a stable sensorless control system under various operating conditions.
KW - Affine projection algorithm (APA)
KW - interior permanent magnet synchronous motor (IPMSM)
KW - online parameter estimation
KW - sensorless control
KW - stator winding resistance and inductance
UR - http://www.scopus.com/inward/record.url?scp=85013073053&partnerID=8YFLogxK
U2 - 10.1109/TPEL.2016.2598731
DO - 10.1109/TPEL.2016.2598731
M3 - Article
AN - SCOPUS:85013073053
SN - 0885-8993
VL - 32
SP - 4631
EP - 4643
JO - IEEE Transactions on Power Electronics
JF - IEEE Transactions on Power Electronics
IS - 6
M1 - 7539360
ER -