Model Order Reduction for Rotating Electrical Machines

  • Zeger Bontinck
  • Oliver Lass
  • Oliver Rain
  • Sebastian Schöps


The simulation of electric rotating machines is both computationally expensive and memory intensive. To overcome these costs, model order reduction techniques can be applied. The focus of this contribution is especially on machines that contain non-symmetric components. These are usually introduced during the mass production process and are modeled by small perturbations in the geometry (e.g., eccentricity) or the material parameters. While model order reduction for symmetric machines is clear and does not need special treatment, the non-symmetric setting adds additional challenges. An adaptive strategy based on proper orthogonal decomposition is developed to overcome these difficulties. Equipped with an a posteriori error estimator, the obtained solution is certified. Numerical examples are presented to demonstrate the effectiveness of the proposed method.



This work is supported by the German BMBF in the context of the SIMUROM project (grant number 05M2013), by the Excellence Initiative of the German Federal and State Governments, and by the Graduate School of Computational Engineering at TU Darmstadt.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Zeger Bontinck
    • 1
  • Oliver Lass
    • 2
  • Oliver Rain
    • 3
  • Sebastian Schöps
    • 1
  1. 1.Technische Universität Darmstadt, Graduate School of Computational EngineeringDarmstadtGermany
  2. 2.Department of Mathematics, Chair of Nonlinear OptimizationTechnische Universität DarmstadtDarmstadtGermany
  3. 3.Robert Bosch GmbHStuttgartGermany

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