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

机译:基于遗传算法和有限元分析的轴向磁通永磁发电机效率和功率密度优化的新方法

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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.
机译:该研究针对输出功率和额定速度幅值为1 kW和100 rpm的低速轴向磁通永磁同步发电机的效率和功率密度提出了一个多目标优化方法。首先,简要介绍了不同的AFPM机器拓扑,并选择了双面内部开槽定子(称为TORUS-S)结构作为当前应用的最合适结构。利用通用的大小方程式来确定最优化问题,然后利用遗传算法。创新地,本研究引入了一种新的适应度函数作为其原始贡献,这为确定目标函数的优先级提供了一种工具。该适应度函数包括两个变量,其中任一变量的增加会导致其中一个目标函数的改善比另一个目标函数的改善。这种方法的优点在需要优先考虑目标功能的情况下尤其明显,就像风轮机中使用的发电机确实确实需要这种情况一样,这种发电机不仅要具有高效率,而且还要减轻重量和体积。最后,通过三维有限元方法对结果进行了验证。

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