An approach based on non-dominated sorting genetic algorithm III for design of permanent magnet synchronous motor

Abstract

Today due to industrial developments, the use of electric motors has increased in all fields. The increase also preceded the development of higher-specification motors. Although weight, cogging torque, torque ripples and drive technology etc. for the working area are important, the demand for the production of highly efficient and cost-effective motors has risen further due to the energy phenomenon in the world. High-quality algorithms are needed to achieve these objectives as well, because electric motor designs are multiparameter and nonlinear engineering problems. This study aims to provide a multi-purpose intelligent design with NSGAII and NSGAIII by selecting outputs such as efficiency and cost of permanent magnet synchronous motor as an objective function. The design was intended for low speed and high torque/volume applications and the motor geometry was thus chosen as surface-mounted and double-layer concentrated winding. The optimization results were tested with a finite element program. Both methods resulted in a 3% increase in efficiency and a 37% reduction in cost versus initial design. Also, according to the results obtained, although NSGA-II and NSGA-III achieved similar results, NSGA-III results showed a more robust and stable course than NSGA-II results. The compatibility of the design optimization and the results of numerical analysis are acceptable and highly satisfactory. So, it provides outputs to demonstrate the features of an electric motor design optimization.