Application of Hybrid SEA in Vehicle NV Package Optimization

<div class="section abstract"><div class="htmlview paragraph">As India’s economy expands and road infrastructure improves, the number of car owners is expected to grow substantially in the coming years. This market potential has intensified competition among original equipment manufacturers (OEMs) to position their products with a focus on cost efficiency while delivering a premium user experience. Noise and Vibration (NV) performance is a critical differentiator in conveying a vehicle's premiumness, and as such, NV engineers must strategically balance the achievement of optimal acoustic performance with constraints on cost, mass, and development timelines.</div><div class="htmlview paragraph">Traditionally, NV package optimization occurs at the prototype or advanced prototype stage, relying heavily on physical testing, which increases both cost and time to market. Furthermore, late-stage design changes amplify these challenges. To address these issues, this paper proposes the integration of Hybrid Statistical Energy Analysis (HSEA) into the early stages of vehicle development, enabling data-driven decision-making from the concept phase. The HSEA model is built by synthesizing experimental calculated SEA parameters and SEA techniques, providing a robust framework for early-stage prediction and validation. Key noise inputs, including engine noise, road noise, are modeled to evaluate their contribution to overall cabin NVH levels. A detailed study is conducted to identify dominant noise paths and component contributions. Inefficient NV components are eliminated, and efficient parts are further analyzed to define their performance thresholds, allowing for optimal specification setting. Based on this analysis, Insertion Loss (IL) and Absorption Coefficient (AC) targets are formulated and communicated to suppliers, ensuring alignment with performance, cost, and development objectives. This approach fosters a more agile NVH development process, reducing prototype dependency and streamlining supplier collaboration.</div></div>