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Altair > Case Studies > Accurate Cabin Predictions: Replacing Physical Testing with Numerical Modeling in Automotive Parts

Accurate Cabin Predictions: Replacing Physical Testing with Numerical Modeling in Automotive Parts

Technology Category

Sensors - Acoustic Sensors
Sensors - Haptic Sensors

Applicable Industries

Automotive
Packaging

Applicable Functions

Product Research & Development
Quality Assurance

Use Cases

Predictive Maintenance
Time Sensitive Networking

Services

Testing & Certification

The Challenge

Trèves Products Services & Innovation, a leading Tier-1 supplier of noise, vibration, and harshness (NVH) reduction parts, was facing a challenge in reducing part design and lead time. The traditional approach required expensive and time-consuming physical testing with real parts to account for their multi-layer arrangement and varying thickness. The input parameters for these models also needed to be readily available. Furthermore, the models had to be comprehensive in scope and easy to implement. With the upcoming reduction in pass-by noise emission limits from 70 to 68 dB, expected in 2024, the ability to accurately predict noise levels became essential. The challenge was to replace physical testing with numerical modeling to meet customer expectations and regulatory requirements.

About The Customer

Trèves Products Services & Innovation is a France-based company with a turnover of €580 million in 2021. As one of the leading Tier-1 suppliers of noise, vibration, and harshness (NVH) reduction parts, Trèves provides full sound packages for the trunk, body, interior, and powertrain. The company employs 4,900 people, including 300 R&D engineers located across 9 technical centers, with 26 plants in 17 countries. They work to meet the requirements of their 15+ OEM customers. Trèves has numerous specialists in the characterization and modeling of poro-elastic sound packages and has been successfully using AlphaCell for over 5 years.

The Solution

Trèves turned to AlphaCell from Matelys-Research Lab, available via the Altair Partner Alliance (APA), to address their challenge. AlphaCell offered several features that met Trèves’ needs, including the ability to predict within seconds the response of multi-layer configurations in diffuse sound field conditions, such as those encountered in an alpha-cabin test. The effect of varying thicknesses was accounted for in a fast, user-friendly manner with any compressed part predicted from the initial material properties. The model’s acoustic input parameters were determined via a dedicated characterization process mastered at Trèves using the Matelys software suite and equipment. Simulation results were easily compared with measured data using the model’s intuitive drag and drop interface. In this project, data for flat samples produced in several thicknesses were compared with real engine hood parts.

Operational Impact

The implementation of the AlphaCell model delivered significant operational benefits for Trèves. The model's ability to predict the response of multi-layer configurations in seconds enabled Trèves to numerically optimize the engine hood solution, replacing the need for physical testing. This not only saved time but also reduced costs associated with manufacturing real parts for testing. Furthermore, the model's intuitive interface allowed for easy comparison of simulation results with measured data, simplifying the process and increasing efficiency. The capabilities of AlphaCell have helped position Trèves to provide even more robust solutions to OEMs in order to achieve the next generation of pass-by noise limits.

Quantitative Benefit

Implemented the model in less than a day, significantly reducing the time compared to manufacturing real parts.
The model can predict the response of multi-layer configurations within seconds, leading to a major time reduction.
The low computation time allowed the modeling process to be applied to the entire sound package, including the engine bay, underbody, and wheel arch area.