Application of genetic algorithms to motor parameter determination

Abstract

This paper applies genetic algorithms to the problem of induction motor parameter determination. Generally available manufacturers published data like starting torque, breakdown torque, full load torque, full load power factor etc, are used to determine the motor parameters for subsequent use in studying machine transients. Results from several versions of the genetic algorithm are presented as well as a comparison with the Newton-Raphson method.

Estimation of Three-Phase Induction Motor Equivalent Circuit Parameters from Manufacturer Catalog Data

“…The final objective in [11] is the calculation of torque and current curves from motor starting to synchronous speed. The authors use GA to search all parameter values of the SCM from starting torque, breakdown torque, full-load torque, full-load power factor and full-load speed.…”

“…Neglecting the magnetizing component of the starting current, R 2 is approximated by (11), which is derived from the expression of air-gap power. Using the starting torque, X 2 results from (12), and X 1 from the X 1 /X 2 ratio.…”

“…GA are once more employed in [11] to determine the SCM and build current and torque curves from catalog data. Four configurations of GA are compared among themselves and to Newton's method, showing that a small deviation on the initial solution can make the latter to diverge while GA are reliable in this context.…”

Multi-objective parameter estimation of induction motor using particle swarm optimization

“…In the recent years, global optimization techniques such as evolutionary algorithm (Nangsue et al, 1999), genetic algorithm (Bishop and Richards, 1990;Alonge et al, 1998;Pillay et al, 1997;Rahimpour et al, 2007;Huang et al, 2001;Nollan et al, 1994;Orlowska Kowalska et al, 2006), adaptive GA (Abdelhadi et al, 2004) and differential evolution (Ursem and Vadstrup, 2003) have been proposed to solve the parameter estimation problems.…”

Application of Evolutionary Algorithms with Adaptive Mutation to the Identification of Induction Motor Parameters at Standstill

“…Few authors proposed evolutionary algorithms (EA) for the identification [1], [2], [6], [9]- [11]. In the most cases simple genetic algorithm (GA) was applied [1], [2], [6], [10], [11]. The proposed EA operated in the binary-coded domain.…”