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Approximate Modeling of Gear Torque of Permanent Magnet Synchronous Motor Based on Improved Latin Hypercube Sampling

机译:基于改进拉丁超立体采样的永磁同步电动机齿轮扭矩近似建模

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摘要

Aim at there are lot of influence factors of the cogging torque of permanent magnet synchronous motor, the orders of magnitude are difference, the approximation modeling error is large, this paper put forward a kind of strong applicability approximate modeling method, can be used for all kinds of motor, namely the isometric cross complementary sampling method, improve the Latin hypercube sampling, improves the approximate model of permanent magnet synchronous motor cogging torque accuracy. In this paper, main influencing factors of cogging torque are determined. Firstly, the initial approximation model was established by the traditional Latin hypercube sampling and Kriging method, and the value range of the input parameters of the sample points whose approximate calculation error exceeded a certain threshold in the sensitivity analysis sample points was obtained. The training set was expanded based on the isometric cross-sampling method, and the calculation accuracy of the approximate modeling was improved. Taking the permanent magnet synchronous motor (PMSM) cogging torque as an example, the method presented in this paper is used for approximate modeling to achieve better calculation accuracy and verify the effectiveness of the method, which lays a foundation for the consistency optimization of PMSM cogging torque.
机译:目的在很多影响永磁同步电动机的齿槽扭矩的影响因素,数量级是差异,近似建模误差大,本文提出了一种强大的适用性近似建模方法,可用于所有各种电机,即等轴承交叉互补采样方法,改善拉丁超立方体采样,改善了永磁同步电动机齿轮扭矩精度的近似模型。本文确定了齿槽扭矩的主要影响因素。首先,通过传统的拉丁超立体采样和Kriging方法建立初始近似模型,并获得了近似计算误差超过了灵敏度分析采样点中的特定阈值的采样点的输入参数的值范围。基于等距交叉采样方法扩展训练集,提高了近似建模的计算精度。以永磁同步电机(PMSM)为例,本文呈现的方法用于近似建模,以实现更好的计算精度并验证该方法的有效性,这为PMSM齿槽的一致性优化奠定了基础扭矩。

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