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Estimation of FEM Model Parameters Using Data Assimilation and Its Application to an Electrical Machine

Archive ouverte : Article de revue

Bacchus, Alexandre | Tounzi, Abdelmounaouim | Argaud, Jean-Philippe | Bouriquet, Bertrand | Biet, Mélisande | Macaire, Ludovic | Le Menach, Y.

Edité par HAL CCSD ; Institute of Electrical and Electronics Engineers

International audience. The goal of this paper is to identify the parameter set of a given electrical machine. The identification method is based on data assimilation coupled with FEM model. Data assimilation method is an optimization approach that limits the space of candidate parameter sets by centering it around those of the ideal machine. An application to an electrical machine is presented based on the analysis of flux sensor signals. The methodology is validated by using twin experiments that consider simulated data and tested considering measurements extracted from the ”real” alternator.

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