A PARAMETER ESTIMATION ALGORITHM FOR INDUCTION MACHINES USING ARTIFICIAL BEE COLONY (ABC) OPTIMIZATION (Nigerian Journal of Technology, 2018)
Conventionally, parameters of the Induction Motor (IM) are determined using the standard no-load and locked rotor test. Performing the no-load test is simple and involved running the machine uncoupled to a load, while measuring the power, voltage, current and shaft speed at different voltage test points. On the other hand, the locked rotor test requires full control of the rotor mechanically in the locked condition before measurements are taken. This paper presents a method for estimating the parameters of IMs without the need for the no-load and locked rotor tests. The method is based on optimization approach using a relatively new swarm based algorithm called the Artificial Bee Colony (ABC) optimization. Two different equivalent circuits are implemented for the parameter estimation scheme; one with parallel and the other with series magnetization circuit. Parameters of a standard 7.5kW IM are estimated using the measured and estimated stator current, input and output power and the power factor. Based on the experimental results obtained, the optimization method using the ABC algorithm gave accurate estimates of the IM parameters when compared to the reference parameters determined using the IEEE standard 112-2004. The maximum errors of -13.730% and 2.249% are obtained for the parallel and series equivalent circuits respectively.  Keywords: Inductions Machines, Parameter Estimation, Artificial Bee Colony, Magnetization Circuit, Optimization Algorithm  http://dx.doi.org/10.4314/njt.v38i1.24