3D GENERATIVE AUTOMATED NVH OPTIMIZATION OF EV MOTOR HOUSING

Wontae Jeong; Daniel Morales-Brotons

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Summary

Paper Title

3D GENERATIVE AUTOMATED NVH OPTIMIZATION OF EV MOTOR HOUSING

Authors

Wontae Jeong
Daniel Morales-Brotons

Modality

Onsite-Oral

Subject area

03.2. Data-driven and Machine Learning Methods for Modeling and Design in Acoustics & Vibration

Publishing Date

25/09/2025

Country of Publishing

Brazil | Brasil

Language of Publishing

Inglês

Paper Page

https://www.even3.com.br/anais/international-congress-exposition-noise-control-engineering/1092524-3d-generative-automated-nvh-optimization-of-ev-motor-housing

ISBN

978-65-272-1573-8

Keywords

Machine Learning, Surrogate Modelling, CAE Data Science, Generative Design, Optimization Loop. Reduced Order Model, Motor, Optimization

Summary

This paper presents an advanced automated optimization framework for the radiated noise performance of electric vehicle (EV) motor housings. The proposed methodology integrates multiple AI-driven techniques to enhance both accuracy and computational efficiency. First, a modal reduced-order model (ROM) enables the rapid generation of training data, allowing real-time updates to the AI prediction model during the optimization process. Second, a 3D shape recognition AI accelerates prediction speed, surpassing conventional CAE-based simulations. Third, a generative design approach utilizing morphing techniques facilitates the creation of diverse candidates for optimized geometries, potentially benefiting from historical designs as well. By seamlessly integrating these components, an efficient optimization workflow is established. The developed framework was applied to an EV motor housing, achieving an NVH prediction accuracy within 2 dB and identifying an optimized design within a single day. This research demonstrates the potential of AI-driven generative optimization combined with reduced-order modeling to accelerate the NVH design process.

Title of the Event: Inter-Noise 2025
City of the Event: São Paulo
Title of the Proceedings of the event: Proceedings of the 54th International Congress and Exposition on Noise Control Engineering
Name of the Publisher: Even3
Means of Dissemination: Meio Digital

How to cite

JEONG, Wontae; MORALES-BROTONS, Daniel. 3D GENERATIVE AUTOMATED NVH OPTIMIZATION OF EV MOTOR HOUSING.. In: Proceedings of the 54th International Congress and Exposition on Noise Control Engineering. Anais...Sao Paulo(SP) WTC Events Center, 2025. Available in: https//www.even3.com.br/anais/international-congress-exposition-noise-control-engineering/1092524-3D-GENERATIVE-AUTOMATED-NVH-OPTIMIZATION-OF-EV-MOTOR-HOUSING. Access in: 07/01/2026