This paper has proposed a low-complexity and discrete-virtual-vector-based predictive current control (DVV-PCC) method based on the bi-subspace. This method can independently adjust the \(d - q\) current components of the \(\alpha - \beta\) subspace and the \(x^{\prime} - y^{\prime}\) current components of the \(x - y\) subspace. The adjustment of the \(\alpha - \beta\) subspace adopts the discrete virtual vector method to match the amplitude of the reference vector, while the adjustment of the \(x - y\) subspace adopts the classical virtual vector method (VV-PCC) to reduce the amplitude of the harmonic currents on the \(x - y\) axis. Experimental results verify the effectiveness of the proposed DVV-PCC method.

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A Low-Complexity and Discrete-Virtual-Vector-Based Predictive Current Control Method for Dual Three-Phase Permanent Magnet Synchronous Motors

  • Jincong Zhu,
  • Qianwen Duan,
  • Qiliang Bao,
  • Yao Mao

摘要

This paper has proposed a low-complexity and discrete-virtual-vector-based predictive current control (DVV-PCC) method based on the bi-subspace. This method can independently adjust the \(d - q\) current components of the \(\alpha - \beta\) subspace and the \(x^{\prime} - y^{\prime}\) current components of the \(x - y\) subspace. The adjustment of the \(\alpha - \beta\) subspace adopts the discrete virtual vector method to match the amplitude of the reference vector, while the adjustment of the \(x - y\) subspace adopts the classical virtual vector method (VV-PCC) to reduce the amplitude of the harmonic currents on the \(x - y\) axis. Experimental results verify the effectiveness of the proposed DVV-PCC method.