scholarly journals A Novel Finite-Control-Set Model Predictive Directive Torque Control Strategy of Permanent Magnet Synchronous Motor with Extended Output

Electronics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 388 ◽  
Author(s):  
Mingxing Du ◽  
Ye Tian ◽  
Wenbai Wang ◽  
Ziwei Ouyang ◽  
Kexin Wei

The performance of conventional direct torque control strategy from the viewpoint of flux and torque ripples has been unsatisfactory. Therefore, this study aims to propose a novel finite-control-set model predictive direct torque control strategy with extended output based on two-step prediction. An appropriate pre-selected vector, which is modulated in a specific manner, is selected through a look-up table and then used to optimise the pre-selected voltage vector based on the computing result from the model prediction and output it. The proposed strategy extends the range of the vectors that can be used to enhance the flux and torque control performance and reduce ripples and computational complexity in comparison with the conventional finite-control-set model predictive direct torque control. The feasibility of the proposed method is verified by conducting a verification test using dSPACE and Tyhpoon HIL 402 experimental platform.

Energies ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 234 ◽  
Author(s):  
GuangQing Bao ◽  
WuGang Qi ◽  
Ting He

A direct torque control (DTC) with a modified finite set model predictive strategy is proposed in this paper. The eight voltage space vectors of two-level inverters are taken as the finite control set and applied to the model predictive direct torque control of a permanent magnet synchronous motor (PMSM). The duty cycle of each voltage vector in the finite set can be estimated by a cost function, which is designed based on factors including the torque error, maximum torque per ampere (MTPA), and stator current constraints. Lyapunov control theory is introduced in the determination of the weight coefficients of the cost function to guarantee stability, and thus the optimal voltage vector reference value of the inverter is obtained. Compared with the conventional finite control set model predictive control (FCS-MPC) method, the torque ripple is reduced and the robustness of the system is clearly improved. Finally, the simulation and experimental results verify the effectiveness of the proposed control scheme.


2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985314 ◽  
Author(s):  
Shi Peicheng ◽  
Wang Suo ◽  
Zhang Rongyun ◽  
Xiao Ping

Considering the difficulty in setting and observing the flux linkage in the existing direct torque control for the brushless direct current motor, which is the cumbersome torque calculation method in direct torque control systems without flux linkage observation, the torque observation, voltage vector selection, and speed loop were studied further in such systems. The fuzzy proportional–integral–derivative direct torque control strategy is presented without flux linkage observation. In terms of torque observation, the cumbersome counter electromotive force calculation method was abandoned, and observation was made combining the three-phase current and Hall signal. In terms of optimal choice of voltage vector, the voltage vector selection table was built using the voltage hysteresis output and Hall signal. In terms of rotation speed control, the adaptive fuzzy proportional–integral–derivative was used to replace the traditional proportional–integral–derivative for the proportional–integral–derivative parameter self-adjustment. A control system simulation model was set up in MATLAB/Simulink for simulation verification. A hardware experimental platform was set up using DSP2812 as the main control board for experimental verification. The research results show that the fuzzy proportional–integral–derivative direct torque control without flux linkage observation further increased the dynamic response rate of the motor speed and reduced the electromagnetic torque ripple amplitude; thus, it is more suitable for application in high-precision and high-stability systems.


2019 ◽  
Vol 29 (2) ◽  
pp. 1-6 ◽  
Author(s):  
Fei Ban ◽  
Guangkun Lian ◽  
Jiahe Zhang ◽  
Biao Chen ◽  
Guobiao Gu

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