The proper orthogonal decomposition (POD) is an efficient model order reduction method, which is frequently coupled with the discrete empirical interpolation method (DEIM) to solve nonlinear electromagnetic problems. A drawback of this method is that instabilities can occur related to the reduction operator of the nonlinear part. In this contribution, different DEIMs and the Gappy POD are employed and analyzed. Consecutively, the methods are employed to efficiently estimate the behavior of a permanent magnet synchronous machine in terms of global quantities, such as torque and iron losses.

中文翻译：

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通过模型降阶对电机行为进行有效估计

适当的正交分解（POD）是一种有效的模型降阶方法，通常与离散经验插值方法（DEIM）结合使用，以解决非线性电磁问题。该方法的缺点是与非线性部分的约简算子可能发生不稳定性。在此贡献中，采用并分析了不同的DEIM和Gappy POD。连续地，这些方法被用于以诸如扭矩和铁损的整体量有效地估计永磁同步电机的性能。