LAPSE:2023.16056
Published Article
LAPSE:2023.16056
An Improved Finite Control Set Model Predictive Current Control for a Two-Phase Hybrid Stepper Motor Fed by a Three-Phase VSI
Chunlei Wang, Dongxing Cao, Xiangxu Qu, Chen Fan
March 2, 2023
In this paper, an improved finite control set model predictive current control (FCS-MPCC) is proposed for a two-phase hybrid stepper motor fed by a three-phase voltage source inverter (VSI). The conventional FCS-MPCC selects an optimal voltage vector (VV) from six active and one null VVs by evaluating a simple cost function and then applies the optimal VV directly to the VSI. Though the implementation is simple, it features a large current ripple and total harmonic distortion (THD). The proposed improved FCS-MPCC builds an extended control set consisting of 37 VVs to replace the original control set with only seven VVs. The increase in the amount of VVs helps to regulate the current more accurately. In each control period, the improved FCS-MPCC takes advantage of deadbeat control to calculate a reference VV, and only the three VVs adjacent to the reference VV are predicted and evaluated, which decrease the computational workload significantly. Build waveform patterns for all VVs in the unbalanced circuit structure to modulate the optimal VV using discrete space vector modulation, which improves the current quality in reducing current ripple and THD. The comparative simulations and experimental results validate the effectiveness of the proposed method.
Keywords
finite control set, Model Predictive Control, stepper motor, voltage source inverter
Suggested Citation
Wang C, Cao D, Qu X, Fan C. An Improved Finite Control Set Model Predictive Current Control for a Two-Phase Hybrid Stepper Motor Fed by a Three-Phase VSI. (2023). LAPSE:2023.16056
Author Affiliations
Wang C: School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China; Tianjin Railway Technical and Vocational College, Tianjin 300240, China [ORCID]
Cao D: School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
Qu X: School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
Fan C: School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China
Journal Name
Energies
Volume
15
Issue
3
First Page
1222
Year
2022
Publication Date
2022-02-08
Published Version
ISSN
1996-1073
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Original Submission
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PII: en15031222, Publication Type: Journal Article
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LAPSE:2023.16056
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doi:10.3390/en15031222
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