Induction Motor model parameter estimation from manufacturer data for use in electromagnetic transient programs

The project will investigate the use of non-linear optimization and heuristic methods such as Genetic algorithms to determine the parameters of commercial induction motors from available manufacturer data. The developed model will be simulated using electromagnetic transients simulation programs. A suitable objective function will be developed which penalizes deviation off the simulation results from manufacturers’ listed values. Parameters for the equivalent circuit will include the inductances and resistances and also the number of windings on the rotor. The optimization algorithm will then attempt to minimize the objective function so as to enforce minimal deviation between the simulated and stated performance. It is necessary because the available data is often incomplete and sometimes contradictory.
The intern will use this research as part of her M.Sc. thesis. The work is of high value to the industry partner RTDS Technologies, as many of their users are facing a problem with obtaining accurate simulation models from available data.

Faculty Supervisor:

Aniruddha M. Gole

Student:

Partner:

RTDS Technologies

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Manitoba

Program: