• DocumentCode
    2369727
  • Title

    Using Quasi-Newton method for energy management in electrical multi source systems

  • Author

    Guemri, Mouloud ; Caux, Stephane ; Ngueveu, Sandra Ulrich

  • Author_Institution
    LAPLACE, UPS, Toulouse, France
  • fYear
    2012
  • fDate
    18-25 May 2012
  • Firstpage
    194
  • Lastpage
    199
  • Abstract
    Finding a compromise for the use of several energy sources in order to meet the power demand of an electrical powertrain system is the objective of energy global optimization. The challenge is to design more efficient algorithms that give better result on consumption costs and require less computing time. The purpose remains to minimize the criterion “hydrogen consumption” whilst satisfying the power demand of the powertrain, by finding an optimal energy splitting strategy between the multi-electrical sources. New heuristics presented in the paper are based on a global optimization approach, have a minimum computing time and more importantly a lower cost consumption than the solutions from the literature, even dynamic programming. Finally, a lower bound of the optimal consumption has been computed and helps to better evaluate the quality of the different solutions proposed.
  • Keywords
    Newton method; energy management systems; hybrid electric vehicles; hydrogen economy; optimisation; power consumption; power transmission (mechanical); consumption costs; electrical multisource system; electrical powertrain system; energy management; energy sources; global optimization; hydrogen consumption; lower bound; minimum computing time; optimal consumption; optimal energy splitting strategy; power demand; quality evaluation; quasiNewton method; Dynamic programming; Equations; Fuel cells; Mechanical power transmission; Optimization; Power demand; Vehicles; Dynamic Programming; Energy; Lower Bound; Management; Off-line Strategy; Quasi-Newton method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environment and Electrical Engineering (EEEIC), 2012 11th International Conference on
  • Conference_Location
    Venice
  • Print_ISBN
    978-1-4577-1830-4
  • Type

    conf

  • DOI
    10.1109/EEEIC.2012.6221572
  • Filename
    6221572