FDB-AOA: An Improved Archimedes Optimization Algorithm

FDB-AOA was developed and validated on Design Optimization of Induction Motor for High Power Fan and Pump Applications

Reducing the losses of electric motors is an important issue that

should be emphasized among the measures to be taken to meet the increasing

efficiency need in the industry. In this sense, when we look at the regulations

published by the EU Energy Commission, we see that the efficiency levels

of electric motors are increasing day by day. Finally, regulation no.

2019/1781 published by the European Union Energy Commission came into

force on 1 July 2021 and the sale of industrial induction engines under

performance class IE3 is prohibited. Various meta-heuristic research

algorithms are used in squirrel cage induction motors (SCIM) design, which

are known to be widely used in industry, to meet European Union Energy

Commission determined efficiency values. In this study, a study to optimize

the design of a 185 kW SCIM was carried out for use in line voltage fan and

compressor applications. In order to obtain a motor in the IE3 efficiency

class, which is the highest efficiency class defined in the IEC 60034-30-1-

2014 standard, the geometric dimensions of the motor have been optimized

using the developed optimization algorithm, taking into account the

minimum cost/maximum efficiency criterion. The Archimedes Optimization

Algorithm (FDB-AOA) based on Fitness Distance Balance was used for the

optimization process. During the optimization process, the MATLAB and

ANSYS Maxwell software were run simultaneously to analyze the

electromagnetic performance of the motor and the objective function. In

order to verify the optimum model obtained as a result of experimental

studies, Finite Element Analysis (FEA) was carried out, the optimum model

was verified and the analysis results were presented. The comparison results

indicate that the optimum design of a 185 kW SCIM has been successfully

achieved thanks to the FDB-AOA algorithm developed in this article.