Inverse Methodology for the Parameter Identification of a Lumped Parameter Thermal Network for an Induction Machine

Pieter Nguyen Phuc, K. Stockman, G. Crevecoeur
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引用次数: 5

Abstract

Thermal modelling of induction machines is becoming increasingly important with the demand for machines with ever increasing efficiency as well as compact design. The lumped parameter thermal model is a flexible and computationally cheap method for the temperature analysis inside an induction machine. However, there are a number of thermal parameter values which are difficult to determine analytically. This includes the air gap convection coefficient, the equivalent radial conductivity of the stator winding and the width of the equivalent air gap between the frame and the stator lamination. In this work, the identification of the thermal model values follows the inverse methodology: assign values to the thermal parameters by aligning temperature measurements at a specific location in the motor with the lumped-parameter model response. Simulation results show that the accuracy of the proposed thermal parameter identification scheme depends on the location of the thermal measurement and more specifically on the sensitivity of the temperature profile with respect to the unknown parameters.
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感应电机集总参数热网络参数辨识的逆方法
随着人们对效率和紧凑设计的要求越来越高,感应电机的热建模变得越来越重要。集总参数热模型是一种灵活且计算成本低廉的感应电机内部温度分析方法。然而,有许多热参数值难以用解析方法确定。这包括气隙对流系数、定子绕组的等效径向电导率和机架与定子层合之间的等效气隙宽度。在这项工作中,热模型值的识别遵循相反的方法:通过将电机中特定位置的温度测量值与集总参数模型响应相匹配,为热参数赋值。仿真结果表明,所提出的热参数识别方案的精度取决于热测量的位置,更具体地说,取决于温度分布对未知参数的灵敏度。
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