Abstract
The parameters of electric machines play a substantial role in the control system which, in turn, has a great impact on machine performance. In this paper, a proposed optimal estimation method for the electrical parameters of induction motors is presented. The proposed method uses the particle swarm optimization (PSO) technique. Further, it also considers the influence of temperature on the stator resistance. A complete experimental setup was constructed to validate the proposed method. The estimated electrical parameters of a 3.8-hp induction motor are compared with the measured values. A heat run test was performed to compare the effect of temperature on the stator resistance based on the proposed estimation method and the experimental measurements at the same conditions. It is shown that acceptable accuracy between the simulated results and the experimental measurements has been achieved.
Highlights
Induction motors (IMs) are employed extensively in several industrial applications because of their simple and rugged structure, easy operation and low cost maintenance
The manuscript has been organized in two main sections; Section 2 presents induction motor parameters estimation based on Particle Swarm Optimization (PSO) algorithm; Section 3 shows the results and discussion using both simulations and experimental systems
An estimation method of induction motor electrical parameters based on the Particle Swarm
Summary
Induction motors (IMs) are employed extensively in several industrial applications because of their simple and rugged structure, easy operation and low cost maintenance. Reference [9] presents the application of PSO for estimating and tracking the changes of IM parameters using measured three phase currents, voltages and rotor speed. This method applied 80 particle numbers and takes about 40 iterations to converge the actual values to the estimated ones. The Particle Swarm Optimization (PSO) algorithm is employed to determine the parameters of inductions motors in several publications, for example, References [18,19,20,21]. The manuscript has been organized in two main sections; Section 2 presents induction motor parameters estimation based on PSO algorithm; Section 3 shows the results and discussion using both simulations and experimental systems
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