The electric motor is a key source of noise in an electric powertrain. Effective Noise, Vibration, and Harshness (NVH) management requires advanced and integrated simulation techniques to identify and mitigate noise and vibration early in the design process. This ensures that electric motors not only deliver optimal performance but also enhance the driving experience with smooth and quiet operation.
In this webinar, we explore how the integration of physics-based simulations and machine learning can optimize NVH at the early stages of electric motor design. Our discussion would be covering the following
- A Complete Integrated Multiphysics Simulation: Electromagnetic analysis of e-motors with consideration of spatial harmonics, inverter design including switching frequency, and vibroacoustic analysis at microphone location.
- Use of Machine Learning: Utilizing GT-SUITE`s in-built Machine Learning Assistant for performing Pre-CAE approach for NVH consideration in early motor design.
- Industrial Use-Case: Highlighting a real-world case study which showcases significant reduction of design cycle time for e-NVH analysis using GT-SUITE.
📅 Join Vinit Kumar and Nakul Joshi on April 16, 2025, at 15:00 IST to gain insights into cutting-edge methodologies that bridge physics and machine learning, advancing electric motor design.