Honda is working to shorten development time and reduce costs by sharing concepts and commonizing parts across vehicle models.

Our team ensures the strength and durability of chassis components and needs fast, accurate load prediction.

We‘ve used Adams simulations to analyse load conditions for each vehicle, but modelling and analysis are time-consuming. Therefore, we built a machine‑learning‑based ROM using ODYSSEE and precomputed simulation data.

The ROM predicts loads and cuts analysis time by over 99%. In this presentation, we introduce how we apply ODYSSEE model to our analysis. We plan to expand this technology to further accelerate product planning and development across the company.

What you will learn:

  • Use ODYSSEE ROM model for the early stage of designing process
  • Workflow to use Adams (system dynamics) analysis results for ML training data
  • Replace Adams analysis with the ODYSSEE ROM model
  • ML techniques contribute to fast vehicle load condition analysis

Register for individual sessions or attend the full series for a complete overview of how AI and machine learning enabled engineering is reshaping the industry.

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