An Improved LPTN Method for Determining the Maximum Winding Temperature of a U-Core Motor

In a traditional lumped-parameter thermal network, no distinction is made between the heat and non-heat sources, resulting in both larger heat flux and temperature drop in the uniform heat source. In this paper, an improved lumped-parameter thermal network is proposed to deal with such problems. The innovative aspect of this proposed method is that it considers the influence of heat flux change in the heat source, and then gives a half-resistance theory for the heat source to achieve the temperature drop balance. In addition, the coupling relationship between the boundary temperature and loading position of the heat generator is also added in the lumped-parameter thermal network, so as to amend the loading position and nodes’ temperature through iterations. This approach breaks the limitation of the traditional lumped-parameter thermal network: that the heat generator can only be loaded at the midpoint, which is critical to determining the maximum temperature in asymmetric heat dissipation. By adjusting the location of heat generator and thermal resistances of each branch, the accuracy of temperature prediction is further improved. A simulation and an experiment on a U-core motor show that the improved lumped-parameter thermal network not only achieves higher accuracy than the traditional one, but also determines the loading position of the heat generator well.