Flux linkage optimization for direct torque control of switched reluctance motor based on model predictive control

2019 ◽  
Vol 14 (7) ◽  
pp. 1105-1113 ◽  
Author(s):  
Chaoyi Shang ◽  
Aide Xu ◽  
Lepeng Huang ◽  
Jiagui Chen
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Direct Torque Control ◽  
Switched Reluctance Motor ◽  
Torque Control ◽  
Flux Linkage ◽  
Switched Reluctance ◽  
Reluctance Motor

scholarly journals Minimization torque ripple for SRM based on flux linkage partition in DB-DTFC

2020 ◽  
Vol 306 ◽  
pp. 04007
Author(s):  
Qianni Li ◽  
Aide Xu ◽  
Chaoyi Shang ◽  
Lepeng Huang
Keyword(s):  
Permanent Magnet Synchronous Motor ◽  
Direct Torque Control ◽  
Torque Ripple ◽  
Torque Control ◽  
Flux Linkage ◽  
Switched Reluctance ◽  
Reluctance Motor ◽  
Calculation Module ◽  
Vector Modulation ◽  
Optimal Space

This paper proposes a novel deadbeat torque and flux control (DB-DTFC) to reduce torque ripple for switched reluctance motor (SRM). DB-DTFC combines the advantages of direct torque control (DTC) and space-vector modulation (SVM). DB-DTFC leads current vector control into DTC in order to find the equation between torque and current through deadbeat prediction theory i.e. a beat reaches a given point. In addition, the deadbeat calculation module here is similar to that of permanent magnet synchronous motor. Based on dq0 reference frame of SRM, the most suitable dq0 axis current of next moment corresponding to different torque errors is calculated and predicted. According to the calculated dq0 axis current, the optimal space voltage vectors can be selected to reduce torque ripple. In order to verify the effectiveness and correctness of the proposed scheme, DB-DTFC is verified and compared with the DTC-SVM by simulation.

scholarly journals Predictive Direct Torque Control of Switched Reluctance Motor for Electric Vehicles Drives

2020 ◽  
Author(s):  
Reyad Abdelfadil ◽  
László Számel
Keyword(s):  
Electric Vehicles ◽  
High Performance ◽  
Direct Torque Control ◽  
Switched Reluctance Motor ◽  
Power Converter ◽  
Torque Control ◽  
Switching Frequency ◽  
Suggested Approach ◽  
Switched Reluctance ◽  
Reluctance Motor

The electrical drive systems utilized in Electric Vehicles (EVs) applications must be reliable and high performance. To providing these specifications, it is essential to design high-efficiency electric motors and develop high-performance controllers. This study introduces direct torque control of Switched Reluctance Motor (SRM) for electric vehicle applications using Model Predictive Control (MPC) technique. The direct torque control using MPC is proposed to maintain the motor torque and motor speed to tracking desired signals with a satisfactory response. In this study, the MPC algorithm was programmed in C- language, and the simulation tests were performed using a non-linear model of 6/4 - 60 kW SRM that is fed with the symmetrical converter. The proposed controller was tested under different load conditions to verify the robustness of the controller, as well as at variable speeds to investigate the tracking performance. Thanks to the proposed method, the SRM torque ripples, stator copper losses, and average switching frequency of the power converter can reduce effectively due to applying a cost function that combines multiple objectives. The obtained outcomes show the effectiveness of the suggested approach compared to conventional direct torque control techniques.

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