A Study on NVH Monitoring Automation using AI/DS
AI/DS-based innovation is taking place in all industries with the aim of maximizing technological innovation and work efficiency, vehicle NVH fields are no exception. In the vehicle NVH test field, NVH development automation and NVH monitoring automation are being carried out with the aim of integrated test automation, and this study is about NVH monitoring automation. The analysis process and results of PG(Proving Ground) driving monitoring automation were examined, and it was confirmed that the NVH performance analysis using one long driving data can be reliably automated. In addition, necessary AI models for outside driving monitoring automation and the expected analysis results are summarized. A methodology for predicting road noise performance is explained using NVH vehicle models using driving big data and deep learning, and the prediction result was represented.
Authors
- Daehun Song
- Cheolkeun Ha (ORCID: https://orcid.org/0000-0003-2454-0848)
- Jun‐Ho Jang (ORCID: https://orcid.org/0000-0003-1590-6414)
- M. S. Lee
Institutions
- Hyundai Motors (South Korea) (KR)
Publication Details
- Journal
- NOISE-CON proceedings
- Published
- 2025-10-22
- DOI
- https://doi.org/10.3397/in_2025_1075717
- Citations
- 1
- Primary Topic
- Vehicle Noise and Vibration Control
- Type
- article
- Field-Weighted Citation Impact
- 0.68