last updated on the 4th of August, 2025
Anton Dan Andrei, Founder and Managing Director, Autoadmin Consulting SRL / Unleashed Engineering
Structural Mechanics, NVH, Machine Learning, Data Science, Artificial Intelligence, System Modelling and Simulation, Simulation Governance, Sensors Modeling
The development of smart tires is reshaping the future of mobility, especially in the context of electric and autonomous vehicles. This paper presents a simulation-driven approach to tire engineering that integrates advanced 3D FEA modeling with sensor signal analysis and big data workflows. Using Abaqus Explicit, we demonstrate how legacy modeling limitations can be overcome to enable system-level design and real-time performance evaluation. Two sensor mounting scenarios are explored, along with the concept of a Virtual Intelligent Tire Belt equipped with multiple acceleration sensors. These configurations generate extensive datasets across varied load cases, highlighting the need for automated post-processing and efficient data management. Our workflow supports the analysis of static and dynamic tire load cases and sensor responses under complex loading conditions. The proposed methodology enables predictive analytics, supports ADAS algorithm development, and aligns with CASE mobility requirements. By combining simulation, automation, and data science, this work offers a scalable solution for smart tire R&D and contributes to the broader goal of engineering innovation in the automotive sector.
Abstract submitted on 04.08.2025.
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