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Adagrad Algorithm based Optimal Slot-pole Selection for Reduced Inductance Harmonics in Concentrated Wound Multiphase PMSM.

机译:基于Adagagrad算法的浓缩缠绕式多相PMSM降低电感谐波的最优槽杆选择。

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Fractional slot concentrated windings (FSCW) permanent magnet synchronous machines (PMSM) have high content of space harmonics in the magnetomotive force (MMF) due to which the harmonic inductance is much larger than the magnetizing inductance [1]. These inductance harmonics lead to high torque ripple and low power factor. In case of FSCW, the coils are full pitched and cannot be chorded like in distributed windings to reduce inductance harmonics and also a suitable rotor structure have small impact on reduction of these harmonics. However, the space harmonic content in the FSCW PMSM vary significantly with the choice of slot-pole combination. Thus, the inductance harmonics can be modeled and minimized using an optimal choice of machine phases (m), stator slot numbers (S) and rotor poles (P). State of the art: [2] has presented the selection of slot, pole and phase numbers for reducing harmonic leakage inductance specifically for single layer CW PMSM. In [3], a detailed procedure for slot-pole selection based on inductances for single and double layer windings are provided. However, these are restricted for odd phase numbers and the selection process is time consuming. In this paper, the impact of winding layers, phase belt, slots, poles, and phase numbers on inductance harmonics has been studied. Further, an Adapative gradient (Adagrad) algorithm based approach is implemented to optimally select these parameters with little prior knowledge about the structural data.
机译:分数槽集中绕组(FSCW)永磁同步机(PMSM)在磁力传递(MMF)中具有高含量的空间谐波(MMF),因为谐波电感远大于磁化电感[1]。这些电感谐波导致高扭矩纹波和低功率因数。在FSCW的情况下,线圈是完全倾斜的,不能像在分布式绕组中一样弦乐,以减少电感谐波,并且合适的转子结构对这些谐波的降低具有很小的影响。然而,FSCW PMSM中的空间谐波含量随着插槽极组合的选择而显着变化。因此,使用机器相(M),定子槽数和转子极(P)的最佳选择,可以建模和最小化电感谐波。最先义:[2]已经提出了选择槽,极和相位数,用于减少单层CW PMSM的谐波漏电感。在[3]中,提供了基于单层绕组的电感的槽极选择的详细过程。但是,这些限制为奇数相位数,选择过程是耗时的。本文研究了绕组层,相位带,槽,杆,杆和相位数的影响已经研究过电感谐波。此外,基于适当的基于梯度(Adagrad)算法的方法,以最佳地选择这些参数,几乎没有关于结构数据的知识。

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