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Uncertainty quantification and sensitivity analysis in electrical machines with stochastically varying machine parameters

Communication avec acte
Auteur
OFFERMANN, Peter
MAC, Hung
NGUYEN, Thu Trang
DE GERSEM, Herbert
HAMEYER, Kay
ccCLENET, Stephane
13338 Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]

URI
http://hdl.handle.net/10985/9556
DOI
10.1109/TMAG.2014.2354511
Date
2015

Résumé

Electrical machines that are produced in mass production suffer from stochastic deviations introduced during the production process. These variations can cause undesired and unanticipated side-effects. Until now, only worst case analysis and Monte-Carlo simulation have been used to predict such stochastic effects and reduce their influence on the machine behavior. However, these methods have proven to be either inaccurate or very slow. This paper presents the application of a polynomialchaos meta-modeling at the example of stochastically varying stator deformations in a permanent-magnet synchronous machine. The applied methodology allows a faster or more accurate uncertainty propagation with the benefit of a zero-cost calculation of sensitivity indices, eventually enabling an easier creation of stochastic insensitive, hence robust designs.

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  • Laboratoire d'Electrotechnique et d'Electronique de Puissance (L2EP) de Lille

Documents liés

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  • Study of the Influence of the Fabrication Process Imperfections on the Performances of a Claw Pole Synchronous Machine Using a Stochastic Approach 
    Article dans une revue avec comité de lecture
    LIU, Sijun; MAC, Hung; MIPO, Jean-Claude; ccCOOREVITS, Thierry; ccCLENET, Stephane (Institute of Electrical and Electronics Engineers, 2015)
    In mass production, fabrication processes of electrical machines are not perfectly repeatable with time, leading to dispersions on the dimensions which are not equal to their nominal values. The issue is then to link the ...
  • Influence of uncertainties on the B(H) curves on the flux linkage of a turboalternator 
    Article dans une revue avec comité de lecture
    MAC, Hung; BEDDEK, Karim; KORECKI, Julien; MOREAU, Olivier; CHEVALLIER, Loic; THOMAS, Pierre; ccCLENET, Stephane (Wiley, 2013)
    In this paper, we analyze the influence of the uncertainties on the behavior constitutive laws of ferromagnetic materials on the behavior of a turboalternator. A simple stochastic model of anhysteretic nonlinear B(H) curve ...
  • Comparison of two approaches to compute magnetic field in problems with random domains 
    Article dans une revue avec comité de lecture
    MAC, Duy Hung; ccCLENET, Stephane; MIPO, Jean-Claude (Institution of Engineering and Technology, 2012)
    Methods are now available to solve numerically electromagnetic problems with uncertain input data (behaviour law or geometry). The stochastic approach consists in modelling uncertain data using random variables. Discontinuities ...
  • Transformation Methods for Static Field Problems With Random Domains 
    Article dans une revue avec comité de lecture
    MAC, Duy Hung; ccCLENET, Stephane; MIPO, Jean-Claude (Institute of Electrical and Electronics Engineers, 2011)
    The numerical solution of partial differential equations onto random domains can be done by using a mapping transforming this random domain into a deterministic domain. The issue is then to determine this one to one random ...
  • Solution of Static Field Problems With Random Domains 
    Article dans une revue avec comité de lecture
    MAC, Duy Hung; MIPO, Jean-Claude; MOREAU, Olivier; ccCLENET, Stephane (Institute of Electrical and Electronics Engineers, 2010)
    A method to solve stochastic partial differential equations on random domains consists in using a one-to-one random mapping function which transforms the random domain into a deterministic domain. With this method, the ...

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