NiCd battery type parameter estimation using a hybrid neuronal approach

  • Authors:

  • L. Merad;M. Bekhti;N. Larbi;A. Boutte

  • Affiliations:

  • Division of Space Instrumentation, National Centre of Space Techniques, Arzew, Algeria;Division of Space Instrumentation, National Centre of Space Techniques, Arzew, Algeria;Division of Space Instrumentation, National Centre of Space Techniques, Arzew, Algeria;Division of Space Instrumentation, National Centre of Space Techniques, Arzew, Algeria

  • Venue:
  • CEA'08 Proceedings of the 2nd WSEAS International Conference on Computer Engineering and Applications
  • Year:
  • 2008

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Abstract

In this study, our principal objective is the estimation of the parameters of a NiCd battery type by using the artificial neural networks. The idea consists in using a hybrid training based on the evolutionary algorithms and the method of Levenberg-Marquardt. The results of simulation show the good founded of the used technique.