• DocumentCode
    2362467
  • Title

    Artificial neural network control and energy management in 42 V DC link

  • Author

    Marie-Francoise, J.N. ; Gualous, H. ; Berthon, A.

  • Author_Institution
    Lab. of Electr. Eng. & Syst., UFC-UTBM
  • fYear
    2005
  • fDate
    11-14 Sept. 2005
  • Abstract
    This paper deals with an experimental realization of a 42 V hybrid power sources for automotive applications. It´s composed by a battery which provides the power in constant mean power and a supercapacitor tank in order to supply power in transient state. Two DC/DC converters are used to adapt voltage and current levels between the 42 V DC link, battery and supercapacitor tank. Voltage is regulated by using artificial neural networks (ANNs)
  • Keywords
    DC-DC power convertors; automotive engineering; energy management systems; neurocontrollers; supercapacitors; 42 V; DC link energy management; DC-DC converters; artificial neural network control; automotive applications; hybrid power sources; supercapacitor tank; transient state; Artificial neural networks; Automotive applications; Batteries; Control systems; DC-DC power converters; Energy management; Intelligent networks; Power supplies; Supercapacitors; Voltage; Automotive application; DC power supply; Energy storage; Energy system management; Neuronal control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics and Applications, 2005 European Conference on
  • Conference_Location
    Dresden
  • Print_ISBN
    90-75815-09-3
  • Type

    conf

  • DOI
    10.1109/EPE.2005.219615
  • Filename
    1665805