Optimized Hybrid Statistical Energy Model for Electric Vehicle Cabin Based on Smooth Domain Methodology

The rapid growth of electric-vehicle (EV) technology makes in-cabin vibration and noise control critical to ride comfort. The high operating frequency of traction motors, combined with the absence of a conventional engine block, intensifies mid-frequency (ca. 500-2000 Hz) vibro-acoustic coupling. Lightweight body structures further complicate control and call for more accurate hybrid finite-element/statistical-energy-analysis (FE-SEA) models. This work integrates an edge-based smoothed finite-element technique (ES-FEM) into a hybrid FE-SEA framework (ES-FE-SEA) to improve boundary continuity and smoothing-domain construction, thereby increasing the accuracy and stability of mid-frequency acoustic-vibration predictions. A reduced-scale cabin model is built in VA One to conduct parametric studies on mesh density, element aspect ratio, mesh type, and damping-loss factor; predictions are assessed with Monte-Carlo analyses. Results show that mesh density strongly affects vibration response, smaller aspect ratios shift peak energy toward higher frequencies, and damping substantially changes both energy levels and peak velocity. The ES-FE-SEA model consistently improves mid-frequency predictions over a conventional FE-SEA formulation and is suitable for acoustic-package optimization and EV-cabin NVH management. Future work will validate model parameters experimentally and extend the framework to multi-physics coupling for broader engineering applicability.