Digital Simulation and Optimization

  • Aerodynamic Flow Visualization and Pressure Mapping on Vehicle Design

  • Multiphysics Simulations of Lithium-Ion Cells

  • Vehicle Dynamics Simulation and Component Optimization

Pausa Play

We leverage cutting-edge simulation technologies to predict system behavior, accelerate design cycles, and reduce development costs—while enhancing accuracy and decision-making.

  • Interactive Aerodynamic Assessment in Vehicle Design: We create integrated workflows that connect vehicle styling and aerodynamic analysis through real-time visualization tools, using fast-response CFD visualization embedded in computer graphics environments. This approach reduces iteration cycles and enhances early aerodynamic performance validation during vehicle body design.
  • ANOVA – DOE – RSM applications: Analysis of variance (ANOVA) is often applied to case sensitive studies (DOE) carried out on schematizations of whole models of vehicles to derive response surfaces (RSMs) representative of their behaviors. The ultimate goal is to: Identify design inconsistencies early on, anticipate the identification of optimal architectural setups/configurations and start CAD modeling phases already knowing optimal geometries and parameters.
  • Neural Networks applications: Neural network models are similarly applied to the vehicle to identify optimal product configurations, simulate and predict the behavior of nonlinear models and define the vehicle architecture based on specific technical requirements. NNs are also applied to live time simulations (vehicle simulator) together with ML and DL suites useful to improve the driver skills during his training on a circuit/use of the virtual mockup of the vehicle.
  • Multiphysics Simulations of Lithium-Ion Cells: Advanced multiphysics simulation models are developed and applied to predict the thermo-electrochemical behavior of lithium-ion battery cells under various operating conditions. This enables optimization of cell design, enhances safety assessment, and supports the development of efficient thermal management strategies for next-generation energy storage systems.