• DocumentCode
    2716318
  • Title

    An optimal control strategy for innovative electric naval propulsion system

  • Author

    Debbou, Mustapha ; Pietrzak-David, Maria

  • Author_Institution
    LAPLACE, Univ. de Toulouse, Toulouse, France
  • fYear
    2015
  • fDate
    March 31 2015-April 2 2015
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    A significant effort to produce more efficient and environmentally-friendly ships has led to the development of certain number of new concepts, of which on board electrification is a very good example. The optimal power management of the propulsion system can lead to a substantial improvement of ship efficiency ensuring both compliance with environmental constraints and lower energy consumption. In this paper, an optimal control strategy is proposed on a new naval propulsion system architecture based on the Double Fed Induction Machine (DFIM). The method is based on the power consumed by the propulsion system; several control techniques are evaluated in order to define a control law assuring lower losses for Voltage Source Inverter (VSI) and gas emissions. A simulation and experimental test are carried out to validate the proposed statements.
  • Keywords
    air pollution; asynchronous machines; electric propulsion; environmental factors; losses; optimal control; power consumption; power convertors; power system management; ships; DFIM; VSI; board electrification; double fed induction machine; energy consumption; environmental constraints; environmentally-friendly ship efficiency; gas emissions; innovative electric naval propulsion system; losses; optimal control law strategy; optimal power management; voltage source inverter; IP networks; Inverters; Lead; Stators; Doubly Fed Induction Machine (DFIM); Propeller; Pulse Width Modulation (PWM); Ship; Stator Flux Oriented Control (SFOC); Voltage Source Inverter (VSI);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ecological Vehicles and Renewable Energies (EVER), 2015 Tenth International Conference on
  • Conference_Location
    Monte Carlo
  • Print_ISBN
    978-1-4673-6784-4
  • Type

    conf

  • DOI
    10.1109/EVER.2015.7113029
  • Filename
    7113029