Genetic algorithm based optimal design for dual-redundancy brushless DC motor

A genetic algorithm (GA) based global optimization for a dual-redundancy brushless DC motor (DR-BLDCM) used in aviation actuators was presented. The aim of the optimal design is to reduce the weight of the motor. First, the objective function was established based on the electromagnetic and thermal models. The electromagnetic models include the flux density and the back-electromotive force coefficient expressed by the analytical method. The thermal models were established by the thermal circuit method, in which an accurate estimation for the iron loss was considered. Then the structural parameters of the dual-redundancy brushless DC motor were optimized by using the GA and taking account of the electromagnetic and thermal characteristic constrains. The result of the optimization shows that the weight of the motor had been reduced by 13.3%. This method can be used as a reference for other motor optimal design.