S&M2882 Research Paper of Special Issue
Published: March 24, 2022
Adaptive Speed Estimation with Genetic Algorithm for Vector-controlled Permanent Magnet Synchronous Motor Drive [PDF]
Yung-Chang Luo, Song-Yi Xie, Chia-Hung Lin, and Ying-Piao Kuo
(Received June 21, 2021; Accepted September 8, 2021)
Keywords: vector-controlled (VC), permanent magnet synchronous motor (PMSM) drive, speed estimation, model reference adaptive system (MRAS), genetic algorithm (GA)
An adaptive speed estimation scheme was established for a vector-controlled (VC) permanent magnet synchronous motor (PMSM) drive. The current and voltage of the stator were used to develop a decoupling VC PMSM drive, and the speed, d-axis, and q-axis stator current control loops were designed using the linear PMSM mathematical model. Hall effect current sensors were used to measure the current of the PMSM. A model reference adaptive system (MRAS) was used to develop a speed estimation scheme based on the reactive power of the PMSM. The pole placement was used to design the d-axis and q-axis stator current controllers, and the speed controller was designed using the genetic algorithm (GA). The MATLAB/Simulink® toolbox was used to establish the simulation scheme, and all the control algorithms were realized by a microprocesser control card. Simulation and experimental results (including the estimated rotor speed, stator current, estimated electromagnetic torque, stator flux position angle, and stator flux locus) confirmed the effectiveness of the proposed approach.Corresponding author: Yung-Chang Luo
This work is licensed under a Creative Commons Attribution 4.0 International License.
Cite this article
Yung-Chang Luo, Song-Yi Xie, Chia-Hung Lin, and Ying-Piao Kuo, Adaptive Speed Estimation with Genetic Algorithm for Vector-controlled Permanent Magnet Synchronous Motor Drive, Sens. Mater., Vol. 34, No. 3, 2022, p. 1191-1201.