Adaptation of the whale optimization algorithm to multi-objective and constrained optimization of the brushless DC motor

This paper presents the algorithm and computer script for the multi-objective and constrained optimization of the brushless DC motors for the propulsion of the electric vehicles. The optimization procedure was developed on the basis of the whale optimization algorithm and tested using the selected benchmark function. The universal analytical model of the brushless DC motor (BLDC) was developed. The designed motor is described by four design variables. The methodology of the two-stage adaptation of the whale optimization algorithm to multi-objective and constrained optimization of the electromagnetic devices are proposed. The developed adaptation improved the efficiency and reliability of the optimization procedure. The multi-objective compromise function contains two functional parameters of the designed motor: efficiency and total materials mass. In the case of the constrained optimization problem, the total mass of the designed motor was minimized and efficiency was maximized, whereas winding temperature was taken into account as a constraints.