An Inverse Modeling Approach for Thermal Properties Estimation in Multi-Layer PMLSMs

Detecting defects and assessing the condition of electrical machines are critical for ensuring their reliability and efficiency. Changes in thermal properties often indicate defects such as thermal aging or delamination. This study introduces an inverse modeling approach designed to estimate internal thermal properties and detect potential defects in multi-layer permanent magnet linear synchronous motors (PMLSMs), subjected to internal heat generation from the coils. A one-dimensional (1D) analytical solution to the non-homogeneous heat equation is derived for the composite layers using the separation of variables method (SVM) and the orthogonal expansion technique (OET). The solution is validated against finite element (FE) simulations, which also serve to create reference temperature datasets required by an inverse heat transfer model (IHTM). The proposed inverse method accurately detects changes in thermal properties and identifies the location and thickness of the delamination layer. Overall, this research confirms the feasibility of monitoring internal thermal property variations with minimized temperature measurements, highlighting its potential for early detection of thermal defects in electrical machines.