TY - GEN
T1 - Sensorless Control of IPMSM Based on Current Prediction and Nonlinear Flux Model
AU - Du, Bochao
AU - Yao, Kai
AU - Wu, Shaopeng
AU - Zhang, Qianfan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Reducing rotor position error is very important for sensorless control of interior permanent magnet synchronous motor (IPMSM). However, classical motor models do not describe nonlinear parameter changes and cross-coupling effects, which lead to rotor position offset errors. To solve this problem, a nonlinear motor incremental inductance model is introduced in this paper. Use the designed polynomial function to fit the flux linkage and incremental inductance. In the low-speed operation region of the motor, the incremental inductance model is applied to the high-frequency voltage injection method, and the current predictive model is used to estimate the rotor position, and finally reduces the rotor position error caused by magnetic saturation and cross-coupling effects, and greatly improves the accuracy of position estimation under low-speed and heavy-load conditions. Finally, the effectiveness and feasibility of the proposed method are verified by experiments.
AB - Reducing rotor position error is very important for sensorless control of interior permanent magnet synchronous motor (IPMSM). However, classical motor models do not describe nonlinear parameter changes and cross-coupling effects, which lead to rotor position offset errors. To solve this problem, a nonlinear motor incremental inductance model is introduced in this paper. Use the designed polynomial function to fit the flux linkage and incremental inductance. In the low-speed operation region of the motor, the incremental inductance model is applied to the high-frequency voltage injection method, and the current predictive model is used to estimate the rotor position, and finally reduces the rotor position error caused by magnetic saturation and cross-coupling effects, and greatly improves the accuracy of position estimation under low-speed and heavy-load conditions. Finally, the effectiveness and feasibility of the proposed method are verified by experiments.
KW - Sensorless control
KW - current prediction model
KW - interior permanent magnet synchronous motor (IPMSM)
KW - nonlinear flux linkage model
UR - https://www.scopus.com/pages/publications/85166187339
U2 - 10.1109/PRECEDE57319.2023.10174321
DO - 10.1109/PRECEDE57319.2023.10174321
M3 - 会议稿件
AN - SCOPUS:85166187339
T3 - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
BT - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
Y2 - 16 June 2023 through 19 June 2023
ER -