Combined method for the cage induction motor parameters estimation using two-stage PSO algorithm

This paper presents a combined method for the equivalent circuit parameters estimation of cage induction motors. The method is based on dual usage of the particle swarm optimization algorithm and the approximation of rotor parameters as a function of the speed, due to the influence of the skin effect. The approximation of rotor parameters as a function of the speed is not directly applied in the parameters estimation algorithm, but it is used to obtain the torque-speed characteristics of cage induction motors. The first stage of the optimization includes the estimation of equivalent circuit parameters of a motor for the nominal operating mode, while the rotor parameters at the start of the motor are estimated in the second stage of the optimization. These parameters are obtained as a result of minimizing the error between the calculated and the manufacture data. The proposed method is applied on eight two-pole induction motors with different rated powers, energy efficiency class IE3, manufactured by ABB. The results are verified by comparing the obtained torque-speed characteristics with the corresponding characteristics provided by the manufacturer (i.e., ABB) using the MotSize program. It is shown that the torque-speed characteristics obtained by the proposed method are in a good agreement with the characteristics given by the manufacturer. Also, the value of the mean absolute relative error does not exceed 5% for all considered motors.