Optimum Design of High-Temperature Superconducting Induction/Synchronous Motor to Increase Torque Density Using Collective Decision Optimization Algorithm

Today, with the high promotion of technology and the expansion of industries, electric motors are used extensively and consume a large part of the electrical energy produced by power plants. Therefore, researchers and experts have always sought solutions to make electric motors with high reliability and low losses. The machines are made of a high temperature superconducting motor with high efficiency are called high temperature superconductor -induction synchronous motor (HTS-ISM). In this paper, the high-temperature superconducting induction/synchronous motor (HTS-ISM) is studied. Optimizing of torque density and the structural dimensions of HTS-ISM is done using one of the newest optimization methods, the collective decision optimization algorithm (CDOA). The results show a torque of about 51.75% increase via the optimization process. Also commonly used optimization method, particle swarm optimization algorithm (PSO) method was implemented to compare the results. The comparison has proved that the CDOA method high capability to optimize the motor design parameters. All of the algorithms in this paper is performed with MATLAB software.