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Uncertainty propagation of iron loss from characterization measurements to computation of electrical machines

Article dans une revue avec comité de lecture
Auteur
BELAHCEN, Anouar
RASILO, Paavo
NGUYEN, Thu Trang
13338 Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
ccCLENET, Stephane
13338 Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]

URI
http://hdl.handle.net/10985/9492
DOI
10.1108/COMPEL-10-2014-0271
Date
2015
Journal
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

Résumé

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. Design/methodology/approach The probabilistic uncertainties in the iron losses are modelled with the spectral approach using chaos polynomials. The Sobol indices are used for the global sensitivity analysis. The machine is modelled with a 2D finite element method and the iron losses are computed with a previously developed accurate method. Findings The uncertainties propagate in different ways to the different components of losses, i.e. eddy current, hysteresis, and excess losses. The propagation is also different depending on the investigated region of the machine, i.e. Stator or rotor teeth, yokes, tooth tips. Research limitations/implications The method does not account for uncertainties related to the manufacturing process, which might result in even larger variability. Practical implications A major implication of the findings is that the identification of iron loss parameters at low frequencies does not affect the loss variability. The identification with high frequency measurement is very important for the rotor tooth tips. The variability in the excess loss parameters is of low impact. Originality/value The presented results are of importance for the magnetic material manufacturers and the electrical machine designers. The manufacturers can plan the measurement and identification procedures as to minimize the output variability of the parameters. The designers of the machine can use the result and the presented procedures to estimate the variability of their design

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

Documents liés

Visualiser des documents liés par titre, auteur, créateur et sujet.

  • Model Order Reduction of Electrical Machines with Multiple Inputs 
    Article dans une revue avec comité de lecture
    FARZAM FAR, M.; BELAHCEN, Anouar; RASILO, Paavo; PIERQUIN, A.; ccCLENET, Stephane (Institute of Electrical and Electronics Engineers, 2017)
    In this paper, proper orthogonal decomposition method is employed to build a reduced-order model from a high-order nonlinear permanent magnet synchronous machine model with multiple inputs. Three parameters are selected ...
  • Model Order Reduction of Electrical Machines with Multiple Inputs 
    Article dans une revue avec comité de lecture
    FARZAM FAR, Mernhaz; BELAHCEN, Anouar; RASILO, Paavo; ccCLENET, Stephane; PIERQUIN, Antoine (Institute of Electrical and Electronics Engineers, 2017)
    In this paper, proper orthogonal decomposition method is employed to build a reduced-order model from a high-order nonlinear permanent magnet synchronous machine model with multiple inputs. Three parameters are selected ...
  • Uncertainty quantification and sensitivity analysis in electrical machines with stochastically varying machine parameters 
    Communication avec acte
    OFFERMANN, Peter; MAC, Hung; NGUYEN, Thu Trang; DE GERSEM, Herbert; HAMEYER, Kay; ccCLENET, Stephane (IEEE, 2015)
    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 ...
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    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 ...
  • Stochastic Metamodel for Probability of Detection Estimation of Eddy-Current Testing Problem in Random Geometric 
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    ABDELLI, Djamel Eddin; NGUYEN, Thanh Hung; CHERIET, Ahmed; ccCLENET, Stephane (Institute of Electrical and Electronics Engineers, 2019)
    The calculation of the Probability Of Detection (POD) in Non Destructive Eddy Current Testing requires the solution of a stochastic model requiring numerous calls of a numerical model leading to a huge computation time. ...

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