A novel approach for efficiency and power density optimization of an Axial Flux Permanent Magnet generator through genetic algorithm and finite element analysis

This study puts forth a multi-objective optimization of the efficiency and power density of a low speed Axial Flux Permanent Magnet (AFPM) synchronous generator with the output power and rated speed amplitude of 1 kW and 100 rpm. Firstly, a brief review of different AFPM machine topologies has been provided and double sided interior slotted stator (known as TORUS-S) structure has been selected as the most suitable structure for the current application. The optimization problem was formulated by means of general sizing equations and then genetic algorithm was utilized. Innovatively, this study introduces a novel fitness function as its original contribution which offers a tool for ascertaining the priority of objective functions. This fitness function includes two variables whereby an increase in either of them leads to more improvement in one of the objective functions than in the other. The merits of this method are especially palpable in situations where it is necessary to prioritize the objective functions as is indeed the case with generators used in wind turbines which should have not only a high efficiency but also a reduced weight and volume. Finally, the results are verified through the three dimensional Finite Element Method.