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Mixed-variable optimal design of induction motors including efficiency, noise and thermal criteria

Optimization and Engineering volume 12, pages 55–72 (2011)Cite this article

Abstract

Squirrel cage induction motors design requires making numerous trade-offs, especially between its audible electromagnetic noise level, its efficiency and its material cost. However, adding the vibro-acoustic and thermal models to the usual electrical model of the motor drastically increases the simulation time. A finite element approach is then inconceivable, especially if the model has to be coupled to an evolutionary optimization algorithm.

A fast simulation tool of the variable-speed induction machine, based on electrical, mechanical, acoustic and thermal analytical models, has therefore been elaborated. It has been validated at different stages with both tests and finite element method (FEM) simulations. This model is then coupled to a mixed-variable constrained Non-dominating Sorting Genetic Algorithm (NSGA-II) with a stochastic repair algorithm. Some global optimizations with respect to several objectives (noise level, efficiency and material cost), including thermal constraints, are finally presented, and several convenient visualizations of multi-dimensional solutions are presented.

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Authors and Affiliations

  1. Cité Scientifique, L2EP, Ecole Centrale de Lille, 59671, Villeneuve d’Ascq, France

    Jean Le Besnerais

  2. LME, Valenciennes, France

    Aurélie Fasquelle

  3. LEC, Université de Technologie de Compiègne, 60200, Compiègne, France

    Vincent Lanfranchi

  4. L2EP, Lille, France

    Michel Hecquet & Pascal Brochet

Authors
  1. Jean Le Besnerais
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  2. Aurélie Fasquelle
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  3. Vincent Lanfranchi
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  4. Michel Hecquet
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  5. Pascal Brochet
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Correspondence to Jean Le Besnerais.

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Le Besnerais, J., Fasquelle, A., Lanfranchi, V. et al. Mixed-variable optimal design of induction motors including efficiency, noise and thermal criteria. Optim Eng 12, 55–72 (2011). https://doi.org/10.1007/s11081-010-9115-1

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  • DOI: https://doi.org/10.1007/s11081-010-9115-1

Keywords

  • Multi-objective optimization
  • Multi-physics modelling
  • Induction machine
  • Magnetic noise
  • Thermal nodal network