Simulation of Electric Machines

Multiphysical modelling, simualtion, optimization

Computer Aided Machine Design

Intensified by the energy transition, efficient and robust designs of electromechanical energy converters, especially electrical machines, are gaining in importance. Be it as a drive or component in the automotive industry, in industrial automation or in household appliances. Machines should be developed close to the technical limit, but this requires transient analyses and uncertainties to be considered early in the design process. Currently, corresponding analyses are often performed late in the development process, so that optimal robust designs may not be considered.

Energy converters are mathematically described by a multiphysics system composed of the electromagnetic field, rotor motion, thermal field, vibrations, and electrical input from a circuit. The modeling leads to a complex coupled system of partial differential algebraic equations, which must be discretized using finite elements, for example.

Research in the group includes problem-specific modelling, model order reduction and analysis that takes uncertainties into account, method development for spatial and time discretization, and parallel simulation and robust optimization.

Parekh, Vivek ; Flore, Dominik ; Schöps, Sebastian (2021):
Deep Learning-based Prediction of Key Performance Indicators for Electrical Machine.
In: IEEE Access, ISSN: 2169-3536, DOI: 10.1109/ACCESS.2021.3053856, ARXIV: 2012.11299. [Article]

Bolten, Matthias ; Friedhoff, Stephanie ; Hahne, Jens ; Schöps, Sebastian (2020):
Parallel-in-Time Simulation of an Electrical Machine using MGRIT.
In: Computing and Visualization in Science, ISSN: 1432-9360, DOI: 10.1007/s00791-020-00333-2, ARXIV: 1912.03106. [Article]

Bontinck, Zeger ; Lass, Oliver ; Schöps, Sebastian ; De Gersem, Herbert ; Ulbrich, Stefan ; Rain, Oliver (2018):
Robust Optimization Formulations for the Design of an Electric Machine.
In: IET Science, Measurement & Technology, 12, (8), pp. 939–948, ISSN: 1751-8822, DOI: 10.1049/iet-smt.2018.5235, ARXIV: 1712.01536. [Article]

Bontinck, Zeger ; Corno, Jacopo ; Schöps, Sebastian ; De Gersem, Herbert (2018):
Isogeometric Analysis and Harmonic Stator-Rotor Coupling for Simulating Electric Machines.
In: Computer Methods in Applied Mechanics and Engineering, 334, pp. 40–55, ISSN: 0045-7825, DOI: 10.1016/j.cma.2018.01.047, ARXIV: 1709.05301. [Article]

Bhat, Prithvi ; Bontinck, Zeger ; Corno, Jacopo ; Schöps, Sebastian ; De Gersem, Herbert (2018):
Modeling of a Permanent Magnet Synchronous Machine Using Isogeometric Analysis.
In: COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 37, (5), pp. 1805–1814, ISSN: 0332-1649, DOI: 10.1108/COMPEL-01-2018-0014, ARXIV: 1708.02409. [Article]

Bontinck, Zeger ; Lass, Oliver ; De Gersem, Herbert ; Schöps, Sebastian (2017):
Uncertainty Quantification for a Permanent Magnet Synchronous Machine with Dynamic Rotor Eccentricity.
In: Progress in Industrial Mathematics at ECMI 2016, volume 26 of The European Consortium for Mathematics in Industry. Springer. ISBN: 978-3-319-63081-6, DOI: 10.1007/978-3-319-63082-3_77. [In Proceedings]

Bontinck, Zeger ; Lass, Oliver ; De Gersem, Herbert ; Schöps, Sebastian (2016):
UQ of a PMSM With Dynamic Rotor Eccentricity and Shape Optimization of its Magnets.
In: XXIV Symposium Electromagnetic Phenomena in Nonlinear Circuits – Proceedings EPNC 2016, 81–82. Poznań, PTETiS Publishers. ISBN: 9788362712045. [In Proceedings]

Bontinck, Zeger ; De Gersem, Herbert ; Schöps, Sebastian (2016):
Response Surface Models for the Uncertainty Quantification of Eccentric Permanent Magnet Synchronous Machines.
In: IEEE Transactions on Magnetics, ISSN: 0018-9464, DOI: 10.1109/TMAG.2015.2491607, Article #7203404. [Article]

Bontinck, Zeger ; Lass, Oliver ; Schöps, Sebastian (2015):
Robust Optimization of a Stochastic Reduced Order Model of a Permanent Magnet Synchronous Machine.
In: ISEF 2015 – XVII International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering. ISBN: 978-84-606-9102-0. [In Proceedings]