Maximum Torque per Volt operation and stability improvement of PMSM in deep flux-weakening Region

Author(s):  
Dakai Hu ◽  
Lei Zhu ◽  
Longya Xu
Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 218 ◽  
Author(s):  
Tae-Gyeom Woo ◽  
Sang-Hoon Lee ◽  
Hak-Jun Lee ◽  
Young-Doo Yoon

This paper presents a flux weakening algorithm for synchronous reluctance motors (SynRMs) based on parameters estimated at standstill. Recently, flux saturated motors have been studied. Flux saturation models were identified and look-up tables were generated based on the saturation model for maximum torque per ampere (MTPA) and flux weakening operations. The operation with tables would degrade the accuracy of operating points when the table size is not enough. The proposed method implements a flux weakening operation without tables, and the operating points are determined with voltages and currents on operating points. Therefore, the accuracy can be maintained. In addition, the computation time to generate the tables is not needed, so the initial commissioning process can be reduced. The proposed method consists of two parts: the determination of a flux weakening region and the modification of current references. The flux weakening region is determined by the angle between direction vectors along the constant torque and voltage decreasing directions in the d-q axis current plane. After identifying the flux weakening region, the current references are modified for flux weakening according to the direction vector and appropriate magnitude. The direction and magnitude are determined by the operating point of the currents and magnitude of the output voltage, respectively. Using the flux saturation model for SynRMs, the flux weakening direction can be determined accurately. As a result, flux weakening can be performed precisely. The experimental results prove the validity of the proposed method.


Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 346
Author(s):  
Faa-Jeng Lin ◽  
Yi-Hung Liao ◽  
Jyun-Ru Lin ◽  
Wei-Ting Lin

An interior permanent magnet synchronous motor (IPMSM) drive system with machine learning-based maximum torque per ampere (MTPA) as well as flux-weakening (FW) control was developed and is presented in this study. Since the control performance of IPMSM varies significantly due to the temperature variation and magnetic saturation, a machine learning-based MTPA control using a Petri probabilistic fuzzy neural network with an asymmetric membership function (PPFNN-AMF) was developed. First, the d-axis current command, which can achieve the MTPA control of the IPMSM, is derived. Then, the difference value of the dq-axis inductance of the IPMSM is obtained by the PPFNN-AMF and substituted into the d-axis current command of the MTPA to alleviate the saturation effect in the constant torque region. Moreover, a voltage control loop, which can limit the inverter output voltage to the maximum output voltage of the inverter at high-speed, is designed for the FW control in the constant power region. In addition, an adaptive complementary sliding mode (ACSM) speed controller is developed to improve the transient response of the speed control. Finally, some experimental results are given to demonstrate the validity of the proposed high-performance control strategies.


2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Saman Toosi ◽  
Mohammad Rezazadeh Mehrjou ◽  
Mahdi Karami ◽  
Mohammad Reza Zare

Interior permanent magnet motor (IPMSM) was used as air conditioner compressor to reduce the power consumption and improve the performance of the system. Two control methods including maximum torque per ampere (MTPA) and flux-weakening methods were employed to increase the speed range of the air conditioner compressor. The present study adapted the flux weakening algorithm technique which can be used for constant torque and constant power regions. Results indicated that the operation speed range of the IPMSM may increase significantly by using the proposed flux weakening algorithm.


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