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A Design Method for the Cogging Torque Minimization of Permanent Magnet Machines with a Segmented Stator Core Based on ANN Surrogate Models

Author

Listed:
  • Elia Brescia

    (Department of Electrical Engineering and Information Technology, Politecnico di Bari, 70126 Bari, Italy)

  • Donatello Costantino

    (Department of Electrical Engineering and Information Technology, Politecnico di Bari, 70126 Bari, Italy)

  • Paolo Roberto Massenio

    (Department of Electrical Engineering and Information Technology, Politecnico di Bari, 70126 Bari, Italy)

  • Vito Giuseppe Monopoli

    (Department of Electrical Engineering and Information Technology, Politecnico di Bari, 70126 Bari, Italy)

  • Francesco Cupertino

    (Department of Electrical Engineering and Information Technology, Politecnico di Bari, 70126 Bari, Italy)

  • Giuseppe Leonardo Cascella

    (Department of Electrical Engineering and Information Technology, Politecnico di Bari, 70126 Bari, Italy)

Abstract

Permanent magnet machines with segmented stator cores are affected by additional harmonic components of the cogging torque which cannot be minimized by conventional methods adopted for one-piece stator machines. In this study, a novel approach is proposed to minimize the cogging torque of such machines. This approach is based on the design of multiple independent shapes of the tooth tips through a topological optimization. Theoretical studies define a design formula that allows to choose the number of independent shapes to be designed, based on the number of stator core segments. Moreover, a computationally-efficient heuristic approach based on genetic algorithms and artificial neural network-based surrogate models solves the topological optimization and finds the optimal tooth tips shapes. Simulation studies with the finite element method validates the design formula and the effectiveness of the proposed method in suppressing the additional harmonic components. Moreover, a comparison with a conventional heuristic approach based on a genetic algorithm directly coupled to finite element analysis assesses the superiority of the proposed approach. Finally, a sensitivity analysis on assembling and manufacturing tolerances proves the robustness of the proposed design method.

Suggested Citation

  • Elia Brescia & Donatello Costantino & Paolo Roberto Massenio & Vito Giuseppe Monopoli & Francesco Cupertino & Giuseppe Leonardo Cascella, 2021. "A Design Method for the Cogging Torque Minimization of Permanent Magnet Machines with a Segmented Stator Core Based on ANN Surrogate Models," Energies, MDPI, vol. 14(7), pages 1-26, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:7:p:1880-:d:526092
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    References listed on IDEAS

    as
    1. Ambra Torreggiani & Claudio Bianchini & Matteo Davoli & Alberto Bellini, 2019. "Design for Reliability: The Case of Fractional-Slot Surface Permanent-Magnet Machines," Energies, MDPI, vol. 12(9), pages 1-18, May.
    2. Diego Calabrese & Gioacchino Tricarico & Elia Brescia & Giuseppe Leonardo Cascella & Vito Giuseppe Monopoli & Francesco Cupertino, 2020. "Variable Structure Control of a Small Ducted Wind Turbine in the Whole Wind Speed Range Using a Luenberger Observer," Energies, MDPI, vol. 13(18), pages 1-23, September.
    3. Marco Palmieri & Salvatore Bozzella & Giuseppe Leonardo Cascella & Marco Bronzini & Marco Torresi & Francesco Cupertino, 2018. "Wind Micro-Turbine Networks for Urban Areas: Optimal Design and Power Scalability of Permanent Magnet Generators," Energies, MDPI, vol. 11(10), pages 1-21, October.
    4. Hui Zhang & Oskar Wallmark, 2017. "Limitations and Constraints of Eddy-Current Loss Models for Interior Permanent-Magnet Motors with Fractional-Slot Concentrated Windings," Energies, MDPI, vol. 10(3), pages 1-19, March.
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    Cited by:

    1. Oktay Karakaya & Murat Erhan Balci & Mehmet Hakan Hocaoglu, 2023. "Minimization of Voltage Harmonic Distortion of Synchronous Generators under Non-Linear Loading via Modulated Field Current," Energies, MDPI, vol. 16(4), pages 1-17, February.
    2. Jelena Loncarski & Vito Giuseppe Monopoli & Vitor Monteiro & Leposava Ristic & Milutin Jovanović, 2022. "Efficiency and Performance Optimization of State-of-the-Art “Multi-Phase, -Level, -Cell, -Port, -Motor” Electrical Drives and Renewable Energy Systems," Energies, MDPI, vol. 15(16), pages 1-3, August.
    3. Pierpaolo Dini & Sergio Saponara, 2022. "Review on Model Based Design of Advanced Control Algorithms for Cogging Torque Reduction in Power Drive Systems," Energies, MDPI, vol. 15(23), pages 1-29, November.
    4. Jie Yu & Youjun Zhang & Hongyuan Shen & Xiaoqin Zheng, 2022. "Adaptive Online Extraction Method of Slot Harmonics for Multiphase Induction Motor," Energies, MDPI, vol. 15(18), pages 1-14, September.

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