Uncertainty quantification and sensitivity analysis in electrical machines with stochastically varying machine parameters
TypeCommunications avec actes
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.
Cette publication figure dans le(s) laboratoire(s) suivant(s)
Visualiser des documents liés par titre, auteur, créateur et sujet.
Global Parameters Sensitivity Analysis and Development of a Two-Dimensional Real-Time Model of Proton-Exchange-Membrane Fuel Cells ZHOU, Daming; NGUYEN, Thu; BREAZ, Elena; ZHAO, Dongdong; CLENET, Stéphane; GAO, Fei (Elsevier, 2018)This paper presents a 2-D real-time modeling approach for a proton-exchange-membrane fuel cell (PEMFC). The proposed model covers multi-physical domains for both ﬂuidic and electrochemical features, which considers in ...
Uncertainty propagation of iron loss from characterization measurements to computation of electrical machines BELAHCEN, Anouar; RASILO, Paavo; NGUYEN, Thu Trang; CLÉNET, Stéphane (Emerald, 2015)The aim of the research is to find out how uncertainties in the characterization of magnetic materials propagate through identification and numerical simulation to the computation of iron losses in electrical machines. ...
Study of the Influence of the Fabrication Process Imperfections on the Performances of a Claw Pole Synchronous Machine Using a Stochastic Approach LIU, Sijun; MAC, Hung; CLENET, Stéphane; COOREVITS, Thierry; MIPO, Jean-Claude (IEEE, 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 ...
MAC, Duy Hung; CLENET, Stéphane; MIPO, Jean-Claude; MOREAU, Olivier (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 ...
Error estimation of a proper orthogonal decomposition reduced model of a permanent magnet synchronous machine HENNERON, Thomas; MAC, Hung; CLENET, Stéphane (IEEE, 2015)Model order reduction methods, like the proper orthogonal decomposition (POD), enable to reduce dramatically the size of a finite element (FE) model. The price to pay is a loss of accuracy compared with the original FE ...