Genetic Algorithm-based Multi-objective Design Optimization of Radial Flux PMBLDC Motor

Genetic algorithm (GA)-based multi-objective optimal design procedure of radial flux permanent magnet brushless DC (PMBLDC) motor is presented in this paper. Three objective functions are considered, i.e., efficiency, weight, and combination of both. The first two fitness functions are single-objective, and the third one is multi-objective. Multi-objective function is combinational function which incorporates both efficiency and weight of the motor into single fitness function. Design of motor is optimized using these three functions separately. Average flux density (B g), torque to rotor volume ratio (K trv), air gap length (l g), motor aspect ratio (A r), and motor split ratio (S r) are design variables to optimize. To validate optimized design obtained from the algorithm, finite element analysis is carried out.