Geometrical permeance network based real-time nonlinear induction machine model

• Author / Creator

  Asghari, Babak

• Real-time digital simulation of electrical machines and drives is an efficient approach to evaluate the true behavior of newly designed machines and controllers before applying them in a real system. State-of-the-art real-time digital simulators aim to offer a precise replica for different parts of an electrical drive. By the aid of these powerful simulators and hardware-in-the-loop (HIL) simulation, design engineers are able to test their new
  controllers or machines against a virtual motor drive which has been previously modeled and tested off-line. Interaction between different parts of the electrical drive, especially under hazardous and abnormal conditions, can then be studied in a cost-effective manner.

  Although many studies about the optimized models of power electronic drives and digital controllers for real-time simulation have been done, the real-time models of electrical machines are still limited to the lumped parameter electric circuit models. This is mainly
  due to the complexity of a detailed electrical machine model which makes it computationally expensive.

  In this thesis geometrical real-time permeance network models (PNMs) of induction machines are developed which can accommodate the local phenomena inside an electric
  machine such as saturation and slotting. For this purpose, numerical methods inside the model are optimized to reduce the computation time. Novel nonlinear solution algorithms
  are also developed to address the problem of real-time simulation of nonlinear systems. Next, the proposed model is linked with other parts of an electric drive to develop a PNM-based real-time induction motor drive. A comparison of the results obtained through real-time simulation and experiment shows their agreement.

• Subjects / Keywords

  • Real-time simulation
  • Squirrel cage induction machine
  • Permeance network model

• Graduation date

  Fall 2011

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R3B31C

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.