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author:

Yan, Chaobin (Yan, Chaobin.) [1] | Yang, Gongde (Yang, Gongde.) [2] (Scholars:杨公德) | Yang, Mingfa (Yang, Mingfa.) [3] (Scholars:杨明发)

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Abstract:

To reduce the computation and complexity of traditional multi-vector model predictive current control (MPCC) algorithm and ensure good control performance, a novel multi-vector MPCC algorithm was proposed to quickly screen the second voltage vector. According to the principle of current non-differential beat control, the d and q-axis current decision factors were defined by the d and q-axis current difference, which simplifies the selection process of the second voltage vector, reduces the calculation of the control chip, and maintains the advantage of low current ripple. On the basis of the new two-vector MPCC algorithm, a novel three-vector MPCC algorithm combining the d and q-axis current decision factors and the effective voltage vector table to directly select the second voltage vector was proposed. Experimental results were presented showing that the new multi-vector MPCC algorithm maintains the control performance of the traditional multi-vector MPCC algorithm while the computation of the new two-vector MPCC algorithm is reduced by 33. 96% and the computation of the new three-vector MPCC algorithm is reduced by 48. 7% . © 2024 Editorial Department of Electric Machines and Control. All rights reserved.

Keyword:

Electric current control Permanent magnets Synchronous motors Vectors

Community:

  • [ 1 ] [Yan, Chaobin](1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China; 2. Fujian Key Laboratory of New Energy Generation and Power Conversion, Fuzhou University, Fuzhou 350108, China)
  • [ 2 ] [Yang, Gongde](1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China; 2. Fujian Key Laboratory of New Energy Generation and Power Conversion, Fuzhou University, Fuzhou 350108, China)
  • [ 3 ] [Yang, Mingfa](1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China; 2. Fujian Key Laboratory of New Energy Generation and Power Conversion, Fuzhou University, Fuzhou 350108, China)

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Source :

Electric Machines and Control

ISSN: 1007-449X

Year: 2024

Issue: 5

Volume: 28

Page: 91-100

Cited Count:

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 1

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