OPTIMAL DESIGN OF A BLDC MOTOR BY GENETIC ALGORITHM

Brushless DC (BLDC) motors are widely used in many applications in the
industry and as such, the design of the motor and its control circuits are very important.
BLDC motor is a permanent magnet motor with electronic commutation. The design
procedures of these motors are much different from that of traditional motors. The
project report describes an optimal design of Brushless DC (BLDC) motor using
Genetic Algorithm (GA) and Simulated Annealing (SA). A constrained optimization on
the objective function is performed and optimal parameters are derived. The resulting
effects of varying GA parameters such as population size, number of generations, and
the amount of mutation and crossover fraction, are also presented for single and multiobjective
functions. In the case of SA technique, the effect of varying number of
iterations on the objective function is analyzed. The design and analysis of the motor
are performed using software tools within the C/C++ programming environment. The
optimal design parameters of the motor obtained by GA are compared with those
obtained by SA technique.

Keyword: Brushless DC motor, genetic algorithm and simulated annealing.