Noise, vibration, and harshness (NVH) validation heavily relies on full vehicle tests and expert knowledge, even when using testing with simulation. And while automotive manufacturers possess a large amount of unused data from previous test campaigns, they rarely revisit it. These resource-intensive test results are a hidden treasure as they are the result of combining design decisions and in-house expertise.
Watch our on-demand webinar to discover how vehicle performance engineers can use historical data and leverage data driven analysis to automate vehicle NVH performance validation — Register now!
Automate vehicle NVH analysis using AI methodologies
Engineers can deploy automated processes by leveraging historical NVH data using artificial intelligence (AI) and machine learning (ML) techniques. This solution enables automotive manufacturers to shorten development cycles and increase overall vehicle and process efficiency. But while deploying AI methodologies for vehicle NVH processes sounds promising, it might be challenging to determine where to start.
Increase efficiency of vehicle NVH testing using AI methods
To realize a successful vehicle design and optimization transformation, NVH engineers need to rely on their expertise and domain knowledge to design specific boundaries for the input data and correctly interpret the output data. They must be able to choose which system responses to extract measurements from and which simulations to use to train the AI algorithm appropriately. When combining this with Simcenter NVH solutions, engineers can gain more insights into full vehicle NVH behavior faster.
Predict NVH performance without creating complex simulation models
Vehicle performance engineers can use data driven NVH analysis to enable enhanced vehicle development by gaining more insights into the NVH behavior of the full vehicle faster. Additional benefits of using Simcenter NVH solutions include:
Increased efficiency of NVH testing using AI methods
Predicting NVH performance without creating complex simulation models
Translating full vehicle targets to subsystems using artificial intelligence
Discover how to integrate AI methodologies in the vehicle development process to speed up NVH data validation and ultimately improve time-to-market — Register to watch the on-demand webinar now!
Meet the speaker
Business Development Manager
Alessandro has been with Siemens Digital Industries Software for 10 years, working in various roles in the Engineering and Consulting Services division. He is currently Business Development Manager responsible for global business development and go-to-market for Engineering Services Solutions, focusing on technologies that combine Test, 1D, and 3D CAE simulation, the automotive and transportation industry, NVH, acoustics, drivability and, ride and handling solutions.