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Cogging Torque Reduction in Brushless Motors by a Nonlinear Control Technique

Author

Listed:
  • Pierpaolo Dini

    (Department of Information Engineering, University of Pisa, Via G. Caruso 16, 56127 Pisa, Italy)

  • Sergio Saponara

    (Department of Information Engineering, University of Pisa, Via G. Caruso 16, 56127 Pisa, Italy)

Abstract

This work addresses the problem of mitigating the effects of the cogging torque in permanent magnet synchronous motors, particularly brushless motors, which is a main issue in precision electric drive applications. In this work, a method for mitigating the effects of the cogging torque is proposed, based on the use of a nonlinear automatic control technique known as feedback linearization that is ideal for underactuated dynamic systems. The aim of this work is to present an alternative to classic solutions based on the physical modification of the electrical machine to try to suppress the natural interaction between the permanent magnets and the teeth of the stator slots. Such modifications of electric machines are often expensive because they require customized procedures, while the proposed method does not require any modification of the electric drive. With respect to other algorithmic-based solutions for cogging torque reduction, the proposed control technique is scalable to different motor parameters, deterministic, and robust, and hence easy to use and verify for safety-critical applications. As an application case example, the work reports the reduction of the oscillations for the angular position control of a permanent magnet synchronous motor vs. classic PI (proportional-integrative) cascaded control. Moreover, the proposed algorithm is suitable to be implemented in low-cost embedded control units.

Suggested Citation

  • Pierpaolo Dini & Sergio Saponara, 2019. "Cogging Torque Reduction in Brushless Motors by a Nonlinear Control Technique," Energies, MDPI, vol. 12(11), pages 1-20, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:11:p:2224-:d:238944
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    Citations

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    Cited by:

    1. Cinzia Bernardeschi & Pierpaolo Dini & Andrea Domenici & Maurizio Palmieri & Sergio Saponara, 2020. "Formal Verification and Co-Simulation in the Design of a Synchronous Motor Control Algorithm," Energies, MDPI, vol. 13(16), pages 1-23, August.
    2. Zhiyan Zhang & Ming Zhang & Jing Yin & Jie Wu & Cunxiang Yang, 2022. "An Analytical Method for Calculating the Cogging Torque of a Consequent Pole Hybrid Excitation Synchronous Machine Based on Spatial 3D Field Simplification," Energies, MDPI, vol. 15(3), pages 1-13, January.
    3. Pierpaolo Dini & Sergio Saponara, 2020. "Design of an Observer-Based Architecture and Non-Linear Control Algorithm for Cogging Torque Reduction in Synchronous Motors," Energies, MDPI, vol. 13(8), pages 1-20, April.
    4. Changchuang Huang & Baoquan Kou & Xiaokun Zhao & Xu Niu & Lu Zhang, 2022. "Multi-Objective Optimization Design of a Stator Coreless Multidisc Axial Flux Permanent Magnet Motor," Energies, MDPI, vol. 15(13), pages 1-13, June.
    5. Rafael de Farias Campos & Cesar da Silva Liberato & José de Oliveira & Tiago Jackson May Dezuo & Ademir Nied, 2022. "Dynamic Strategy for Effective Current Reduction in Brushless DC Synchronous Motors Fault Tolerant Operation," Energies, MDPI, vol. 15(24), pages 1-17, December.
    6. Feifan Ji & Qingyu Song & Yanjun Li & Ran Cao, 2023. "An Accurate Torque Control Strategy for Permanent Magnet Synchronous Motors Based on a Multi-Closed-Loop Regulation Design," Energies, MDPI, vol. 17(1), pages 1-19, December.
    7. Massimo Caruso & Antonino Oscar Di Tommaso & Rosario Miceli & Fabio Viola, 2022. "A Cogging Torque Minimization Procedure for Interior Permanent Magnet Synchronous Motors Based on a Progressive Modification of the Rotor Lamination Geometry," Energies, MDPI, vol. 15(14), pages 1-19, July.
    8. Ze Jiang & Xiaoyan Huang & Wenping Cao, 2022. "RLS-Based Algorithm for Detecting Partial Demagnetization under Both Stationary and Nonstationary Conditions," Energies, MDPI, vol. 15(10), pages 1-17, May.
    9. 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.
    10. Kamila Jankowska & Mateusz Dybkowski, 2021. "A Current Sensor Fault Tolerant Control Strategy for PMSM Drive Systems Based on C ri Markers," Energies, MDPI, vol. 14(12), pages 1-18, June.
    11. Pierpaolo Dini & Sergio Saponara, 2020. "Design of Adaptive Controller Exploiting Learning Concepts Applied to a BLDC-Based Drive System," Energies, MDPI, vol. 13(10), pages 1-20, May.
    12. Wenyi Li & Yalin Wang & Yi Ding & Yi Yin, 2022. "Optimization Design of Packaging Insulation for Half-Bridge SiC MOSFET Power Module Based on Multi-Physics Simulation," Energies, MDPI, vol. 15(13), pages 1-19, July.
    13. Lucian Mihet-Popa & Sergio Saponara, 2021. "Power Converters, Electric Drives and Energy Storage Systems for Electrified Transportation and Smart Grid Applications," Energies, MDPI, vol. 14(14), pages 1-5, July.
    14. Marcel Nicola & Claudiu-Ionel Nicola, 2022. "Improvement of Linear and Nonlinear Control for PMSM Using Computational Intelligence and Reinforcement Learning," Mathematics, MDPI, vol. 10(24), pages 1-34, December.
    15. Chaelim Jeong & Dongho Lee & Jin Hur, 2019. "Mitigation Method of Slot Harmonic Cogging Torque Considering Unevenly Magnetized Permanent Magnets in PMSM," Energies, MDPI, vol. 12(20), pages 1-15, October.
    16. T. A. Anuja & M. Arun Noyal Doss, 2021. "Reduction of Cogging Torque in Surface Mounted Permanent Magnet Brushless DC Motor by Adapting Rotor Magnetic Displacement," Energies, MDPI, vol. 14(10), pages 1-20, May.

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