An Improved Model Predictive Control Method for Permanent Magnet Synchronous Motor with a Spatial Geometry-Based Cost Function
ID:66 View Protection:ATTENDEE Updated Time:2022-11-02 17:54:58 Hits:214 Oral Presentation

Start Time:2022-11-04 10:30(Asia/Shanghai)


Session:M Electric Machine Design and Control » PS2Poster Session 2

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As the single-vector model predictive control (MPC) for permanent magnet synchronous motor (PMSM) has large current ripples, an improved MPC strategy for PMSM with a spatial geometry-based cost function is proposed to reduce the current ripples. First, a new spatial geometry-based objective function is presented, which is aiming at reducing the geometrical distance between the given current vector and the calculated actual one. Next, 12 adjustable virtual voltage vectors are constructed based on the 8 basic voltage vectors with the assumption that the duration time of each basic voltage vector is inversely proportional to its corresponding cost function value. By using these adjustable virtual voltage vectors, the current ripples are reduced accordingly. Additionally, a new voltage vector preselection method is also proposed based on the defined virtual voltage vectors aiming at reducing the calculation amount. Moreover, a detailed theoretical analysis is carried out based on the spatial geometry of the voltage vectors as well as the presented cost function, and the effectiveness of this strategy is validated theoretically. Contrastive simulation analyses verified the effectiveness of this strategy.
Model predictive control (MPC),permanent magnet synchronous motor (PMSM),theoretical analysis,effectiveness validation
PengShuai Wang
Zhengzhou University of Light Industry

Submission Author
Pengshuai Wang Zhengzhou University of Light Industry
Leilei Guo College of Electrical and Information Engineering; Zhengzhou University of Light Industry
Yanyan Li Zhengzhou University of Light Industry
Xueyan Jin Zhengzhou University of Light Industry
Changzhou Yu Hefei University
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    Nov 03



    Nov 05


  • Aug 01 2022

    Draft paper submission deadline

  • Nov 05 2022

    Contribution Submission Deadline

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