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Experimental validation of a geometrical nonlinear permeance network based real-time induction machine model

机译:基于几何非线性渗透网络的实时感应机模型的实验验证

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Real-time digital simulation of electrical machines and drives is a cost-effective approach to evaluate the true behavior of newly designed machines and controllers before applying them in a real system. Although many studies exist regarding the optimized models of power electronic drives and digital controllers for real-time simulation, the real-time models of electrical machines are still limited to the lumped parameter electric circuit models. This is mainly due to the complexity of a detailed electrical machine model which makes it computationally expensive. This paper presents the modeling, real-time implementation, finite element analysis, and experimental validation of a nonlinear geometrical permeance network based induction machine model. A nonlinear permeance network model (PNM) is developed for the real-time simulation of a 3 hp squirrel cage induction machine (SCIM) with closed rotor slots. Several studies both under open-loop and closed-loop control conditions are conducted and the results obtained from the off-line and realtime simulations and the experiment are compared with each other to show the effectiveness of the proposed PNM model.
机译:电机和驱动器的实时数字仿真是一种经济高效的方法,可以在将新设计的机器和控制器应用于在真实系统中应用之前的真正行为。虽然存在关于电力电子驱动器和数字控制器的优化模型的许多研究,但是电机的实时模型仍然限于集总参数电路模型。这主要是由于详细电机模型的复杂性,使其计算得昂贵。本文介绍了非线性几何渗透网络基于电机模型的建模,实时实现,有限元分析和实验验证。非线性渗透网络模型(PNM)是为具有闭合转子槽的3 HP鼠笼式感应机(SCIM)的实时仿真而开发的。在开环和闭环控制条件下进行了几项研究,并彼此比较了从离线和实时模拟中获得的结果,以显示所提出的PNM模型的有效性。

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