Transient simulation of an electrical rotating machine achieved through model order reduction

被引:0
作者
Montier L. [1 ,2 ]
Henneron T. [3 ]
Clénet S. [1 ]
Goursaud B. [2 ]
机构
[1] L2EP - Laboratoire d’Electrotechnique et d’Electronique de Puissance, Arts et Métiers ParisTech, 8 Boulevard Louis XIV, Lille
[2] THEMIS, EDF R&D, 1 Avenue du Général de Gaulle, Clamart
[3] L2EP - Laboratoire d’Electrotechnique et d’Electronique de Puissance, Univ. Lille, Laboratoire L2EP, Cité Scientifique, Bâtiment P2, Villeneuve d’Ascq
关键词
Discrete empirical interpolation method; Finite element method; Model order reduction; Overlapping finite element method; Proper orthogonal decompostion; Synchronous machine;
D O I
10.1186/s40323-016-0062-z
中图分类号
学科分类号
摘要
Model order reduction (MOR) methods are more and more applied on many different fields of physics in order to reduce the number of unknowns and thus the computational time of large-scale systems. However, their application is quite recent in the field of computational electromagnetics. In the case of electrical machine, the numerical model has to take into account the nonlinear behaviour of ferromagnetic materials, motion of the rotor, circuit equations and mechanical coupling. In this context, we propose to apply the proper orthogonal decomposition combined with the (Discrete) empirical interpolation method in order to reduce the computation time required to study the start-up of an electrical machine until it reaches the steady state. An empirical offline/online approach based on electrical engineering is proposed in order to build an efficient reduced model accurate on the whole operating range. Finally, a 2D example of a synchronous machine is studied with a reduced model deduced from the proposed approach. © 2016, The Author(s).
引用
收藏
相关论文
共 50 条
[31]   VBR electromagnetic transient fast simulation model of synchronous machine based on time scale transformation [J].
Shu-Jun, Yao ;
Peng, Zhan ;
Shuo, Zhang ;
Wan-Huai, Guo .
JOURNAL OF ENGINEERING-JOE, 2019, (16) :996-1000
[32]   On the order reduction of the radiative heat transfer model for the simulation of plasma arcs in switchgear devices [J].
Fagiano, Lorenzo ;
Gati, Rudolf .
JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER, 2016, 169 :58-78
[33]   Acoustic simulation of cavities with porous materials using an adaptive model order reduction technique [J].
Xie, Xiang ;
Zheng, Hui ;
Jonckheere, Stijn ;
Desmet, Wim .
JOURNAL OF SOUND AND VIBRATION, 2020, 485
[34]   Model order reduction for circuit level simulation of RF MEMS frequency selective devices [J].
Del Tin, L. ;
Greiner, A. ;
Korvink, J. G. .
SENSOR LETTERS, 2008, 6 (01) :1-8
[35]   SystemC-AMS Simulation of a Biaxial Accelerometer based on MEMS Model Order Reduction [J].
Vernay, Benoit ;
Krust, Arnaud ;
Schropfer, Gerold ;
Pecheux, Francois ;
Louerat, Marie-Minerve .
2015 SYMPOSIUM ON DESIGN, TEST, INTEGRATION AND PACKAGING OF MEMS/MOEMS (DTIP), 2015,
[36]   Multiphysical Simulation, Model Order Reduction (ECSW) and Experimental Validation of an Active Magnetic Bearing [J].
Maierhofer, Johannes ;
Dietz, Christoph ;
Zobel, Oliver M. ;
Rixen, Daniel J. .
ACTUATORS, 2022, 11 (06)
[37]   Model order reduction for numerical simulation of particle transport based on numerical integration approaches [J].
Geiser, Juergen .
MATHEMATICAL AND COMPUTER MODELLING OF DYNAMICAL SYSTEMS, 2014, 20 (04) :317-344
[38]   Implementation of Simplified Model Order Reduction Based on POD for Dynamic Simulation of Electric Motors [J].
Okamoto, Kazuya ;
Sakamoto, Hiroki ;
Igarashi, Hajime .
2019 22ND INTERNATIONAL CONFERENCE ON THE COMPUTATION OF ELECTROMAGNETIC FIELDS (COMPUMAG 2019), 2019,
[39]   Dictionary-based Model Order Reduction via POD-DEIM with Support Vector Machine for the Parametrized Burgers' Equation [J].
Sukuntee, Norapon ;
Chaturantabut, Saifon .
THAI JOURNAL OF MATHEMATICS, 2022, :38-52
[40]   Design sensitivity analysis for transient responses of viscoelastically damped systems using model order reduction techniques [J].
Zhe Ding ;
Junlei Shi ;
Qiang Gao ;
Qianwen Huang ;
Wei-Hsin Liao .
Structural and Multidisciplinary Optimization, 2021, 64 :1501-1526