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PMSM Model Predictive Control Strategy Based on Improved Virtual Space Vector Method
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Shaoqi WAN1, Bo WANG2, Wenqing GUAN2, Jingbo CHEN2, Congxin LÜ1, Haiying DONG1
Electric Drive | 2024, 54(12) : 8 - 15
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Electric Drive | 2024, 54(12): 8-15
PMSM Model Predictive Control Strategy Based on Improved Virtual Space Vector Method
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Shaoqi WAN1, Bo WANG2, Wenqing GUAN2, Jingbo CHEN2, Congxin LÜ1, Haiying DONG1
Affiliations
  • 1 College of New Energy and Power Enginering，Lanzhou Jiaotong University，Lanzhou 730070，Gansu，China
  • 2 Lanzhou Wanli Airlines Electromechanical Limited Liability Company，Lanzhou 730070，Gansu，China
Published: 2024-12-20 doi: 10.19457/j.1001-2095.dqcd25229
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The traditional control of electromechanical actuator in aviation electromechanical servo system mostly adopts two-level inverter and PID control，which can not achieve higher precision control of permanent magnet synchronous motor. In view of the above problems and the difficulty of space vector modulation algorithm to solve the problem of neutral point voltage balance，a model predictive control method based on improved virtual space vector method was proposed，and the corresponding control strategy was designed. The model predictive control was used to improve the control response speed and control accuracy of the permanent magnet synchronous motor. The neutral point clamped（NPC） three-level inverter with more sinusoidal output was used. The improved virtual space vector pulse width modulation（VSVPWM） was used to construct a dodecagon virtual space vector diagram closer to the vector circle. The simulation results show that the improved method can realize the stable operation of permanent magnet synchronous motor under low torque ripple，and has a good control effect on the midpoint voltage balance problem.

three-level inverter  /  midpoint potential  /  model predictive control  /  virtual voltage vector
Shaoqi WAN, Bo WANG, Wenqing GUAN, Jingbo CHEN, Congxin LÜ, Haiying DONG. PMSM Model Predictive Control Strategy Based on Improved Virtual Space Vector Method[J]. Electric Drive, 2024 , 54 (12) : 8 -15 . DOI: 10.19457/j.1001-2095.dqcd25229
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Year 2024 volume 54 Issue 12
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Article Info
doi: 10.19457/j.1001-2095.dqcd25229
  • Receive Date：2023-07-10
  • Online Date：2025-12-10
  • Published：2024-12-20
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  • Received：2023-07-10
  • Revised：2023-10-16
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Affiliations
    1 College of New Energy and Power Enginering，Lanzhou Jiaotong University，Lanzhou 730070，Gansu，China
    2 Lanzhou Wanli Airlines Electromechanical Limited Liability Company，Lanzhou 730070，Gansu，China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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