Accurate Prediction of the Mechanical Properties of Welded/Interlocked Motor Core for Reliable NVH Analysis

Accurate prediction of the mechanical properties of welded and interlocked motor cores is critical for reliable NVH analysis of electric drives. Unlike glue-laminated cores, which rely on adhesive bonding and exhibit relatively uniform stiffness distributions, welded or mechanically interlocked laminations introduce strong local discontinuities due to spot welds, contacts, or interlocking features. These connections significantly alter the load transfer paths across laminations, resulting in anisotropic stiffness behavior and localized stress concentrations that cannot be accurately captured by homogenization approaches developed for glue-laminated cores. To address this, a refined unit-cell (RVE) modeling framework is proposed, which explicitly incorporates welded or interlocked regions as discrete mechanical connections within the periodic lamination structure. The framework accounts for variations in weld spacing/size, interlaminar contact, and interlock geometry, enabling the derivation of effective elastic constants and shear moduli that represent the global behavior of the welded stack. Finite element simulations are conducted on representative RVE models, and the predicted effective properties are compared with experimental modal and static test data from production motor cores. The results show that the presence of welds increases out-of-plane stiffness but reduces damping relative to glue-laminated cores, which in turn leads to distinct NVH characteristics such as higher natural frequencies and more pronounced vibration transmission. The proposed method thus provides a systematic way to capture the mechanical distinctiveness of welded/interlocked laminations while maintaining computational efficiency for large-scale NVH simulations. This work offers an essential extension of RVE-based homogenization methods, ensuring reliable prediction of welded core behavior for motor NVH performance optimization.