• DocumentCode
    1845676
  • Title

    Effective FPGA-based electric motor modeling with floating-point cores

  • Author

    Bachir, Tarek Ould ; David, Jean-Pierre ; Dufour, Christian ; Belanger, Jean

  • Author_Institution
    Dept. of Electr. Eng., Ecole Polytech. de Montreal, Montréal, QC, Canada
  • fYear
    2010
  • fDate
    7-10 Nov. 2010
  • Firstpage
    829
  • Lastpage
    834
  • Abstract
    The simulation of electromechanical systems like motor drives often requires sub-microsecond calculation timesteps considering the fast dynamic of such systems and the high-switching frequency involved. Migrating computational load to an FPGA processor has proven to effectively meet the real-time simulation needs of such systems. However, many challenges still must be overcome before broad adoption of FPGA technology for real-time simulation applications occurs. In this paper, a general framework is presented for effective use of FPGA machine drive modeling when the state-space approach is used. Computations are performed in floating-point using commercially available arithmetic cores. Using the discussed framework guarantees that time steps well below 1 μs can be achieved. Two real-world applications examples are given in the paper: an FPGA-based implementation of a BLDC motor, and an FPGA-based implementation of an induction motor.
  • Keywords
    brushless DC motors; field programmable gate arrays; induction motor drives; state-space methods; BLDC motor; FPGA machine drive modeling; FPGA processor; arithmetic cores; electric motor modeling; electromechanical system simulation; floating-point cores; high-switching frequency; induction motor; motor drives; real-time simulation; state-space approach; Adders; Computational modeling; Field programmable gate arrays; Inductance; Mathematical model; Real time systems; System-on-a-chip;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society
  • Conference_Location
    Glendale, AZ
  • ISSN
    1553-572X
  • Print_ISBN
    978-1-4244-5225-5
  • Electronic_ISBN
    1553-572X
  • Type

    conf

  • DOI
    10.1109/IECON.2010.5675179
  • Filename
    5675179