Milad N. Azari
Brushless DC, optimal design, collective decision optimization algo-rithm (CDOA), cost function
Today, electric motors are widely used in all industries, and most of the equipment is equipped with a variety of electric motors. Brushless DC (BLDC) motors are one of the most popular one in recent years. The use of these motors in sensitive applications is due to the advantages of low noise, precision operation, precise control of speed, torque and flexibility in its structure and shape. Due to the sensitive applications of this motor, the design of the motor in the lowest volume and maximum efficiency is very important. In this paper, the optimal design of the BLDC motor is investigated using collective-based intelligence algorithms, and a new method is proposed to optimize and reduce simultaneously the volume, losses and cost of building a DC motor without brushes using a collective decision optimization algorithm (CDOA). In general, optimizing the process of finding optimal values for a system or mathematical model is said to be among all possible answers with the maximization approach or minimization of the objective function. In the CDOA, human behaviour is based on the steps and characteristics, such as various decision-making that involves a process based on experience, a stage based on others, a group-based thinking, a leader-based stage and a simulation based on the creativity stage, and shows the optimal response. The simulation results show the proposed methods have a good performance and have been able to find the geometric parameters of the BLDC motor so that the volume, cost and motor losses are minimized.
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