Gauss-PSO Parameter Identification Algorithm for Single-Phase Induction Motors

This paper proposes a new parameter identification approach for a single-phase induction motor (SPIM) whose parameters are usually obtained using several traditional techniques such as the DC, no-load, load and locked-rotor tests. It can be realized that the traditional techniques are complicated and require a higher cost with extra equipment. The proposal is based on using a Gauss particle swarm optimization (Gauss-PSO) algorithm. The Gauss-PSO algorithm modifies the algorithm parameters to improve the performance of the standard PSO algorithm. The algorithms use the experimental measurements of the currents and active powers in the SPIM main and auxiliary windings as the inputs to the parameter estimator. The experimental results obtained compare the identified SPIM parameters with the SPIM parameters achieved using the traditional tests. There is also a comparison of the solution quality between the standard PSO and Gauss-PSO algorithms. The results show that the Gauss-PSO algorithm is better than the standard PSO algorithm for parameter identification of the SPIM.