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Multi-Stage Optimization of Induction Machines Using Methods for Model and Parameter Selection

Author

Listed:
  • Martin Nell

    (Institute of Electrical Machines—IEM, RWTH Aachen University, 52062 Aachen, Germany)

  • Alexander Kubin

    (Institute of Electrical Machines—IEM, RWTH Aachen University, 52062 Aachen, Germany)

  • Kay Hameyer

    (Institute of Electrical Machines—IEM, RWTH Aachen University, 52062 Aachen, Germany)

Abstract

Optimization methods are increasingly used for the design process of electrical machines. The quality of the optimization result and the necessary simulation effort depend on the optimization methods, machine models and optimization parameters used. This paper presents a multi-stage optimization environment for the design optimization of induction machines. It uses the strategies of simulated annealing, evolution strategy and pattern search. Artificial neural networks are used to reduce the solution effort of the optimization. The selection of the electromagnetic machine model is made in each optimization stage using a methodical model selection approach. The selection of the optimization parameters is realized by a methodical parameter selection approach. The optimization environment is applied on the basis of an optimization for the design of an electric traction machine using the example of an induction machine and its suitability for the design of a machine is verified by a comparison with a reference machine.

Suggested Citation

  • Martin Nell & Alexander Kubin & Kay Hameyer, 2021. "Multi-Stage Optimization of Induction Machines Using Methods for Model and Parameter Selection," Energies, MDPI, vol. 14(17), pages 1-24, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5537-:d:629237
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    References listed on IDEAS

    as
    1. L. Ingber, 1989. "Very fast simulated re-annealing," Lester Ingber Papers 89vf, Lester Ingber.
    2. Gang Lei & Jianguo Zhu & Youguang Guo & Chengcheng Liu & Bo Ma, 2017. "A Review of Design Optimization Methods for Electrical Machines," Energies, MDPI, vol. 10(12), pages 1-31, November.
    3. Martin Nell & Alexander Kubin & Kay Hameyer, 2021. "Approach for the Model and Parameter Selection for the Calculation of Induction Machines," Energies, MDPI, vol. 14(18), pages 1-20, September.
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    Cited by:

    1. Ryszard Palka, 2022. "The Performance of Induction Machines," Energies, MDPI, vol. 15(9), pages 1-4, April.
    2. Martin Nell & Alexander Kubin & Kay Hameyer, 2021. "Approach for the Model and Parameter Selection for the Calculation of Induction Machines," Energies, MDPI, vol. 14(18), pages 1-20, September.

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