Design optimization for torque density in brushless DC motor with IPM V-type using PSO Method

Abstract

The analysis model is the first stage used to determine the design parameters of the motor. It is coupled with an optimization method to find a combination of design parameters. The purpose of this paper is optimizing the torque density of the Brushless DC (BLDC) Motor with Interior Permanent Magnet (IPM) V-type. The reference design is 3-phase and 12/8 pole BLDC motor with a concentrated winding. To obtain this optimal design, this is done by eliminating the rotor area that is not covered by magnetic flux without reducing the main performance of the motor. Elimination area prediction refers to initial motor design simulation which is operated on rating condition. Mathematical modeling is based on the 2-D finite element analysis (FEA) using software Ansys Maxwell. Particle Swarm Optimization (PSO) algorithm with multi-objective function has been applied to determine the area of the rotor structure to be eliminated, resulting in an optimal torque-density design. Matlab code is also included to execute the optimization algorithm. Excitation uses the ideal sinusoidal signal by ignoring harmonic distortion. This paper features a new optimal design for IPM by considering torque density, cogging torque, harmonic distortion in back-electromagnetic force (back-EMF), and material demagnetization constraints using PSO. Quality of PSO optimization can be proven by increasing the torque density without compromising the main performance of the motor compared with FEA. With this method also provide disadvantage, such as the cost of production is more expensive because it should add a profile of the rotor mold.