  The performance of Newton-Raphson, Levenberg-Marquardt, Damped Newton-Raphson
and genetic algorithms are investigated for the estimation of induction motor
equivalent circuit parameters from commonly available manufacturer data. A new
hybrid algorithm is then proposed that combines the advantages of both descent
and natural optimisation algorithms. Through computer simulation, the hybrid
algorithm is shown to significantly outperform the conventional algorithms in
terms of convergence and squared error rates. All of the algorithms are tested
on a large data set of 6,380 IEC (50Hz) and NEMA (60Hz) motors.
