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AI with Model-Based Design: Virtual Sensor Modeling

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Why This Matters

This webinar highlights the importance of AI-driven virtual sensors in enhancing system design and diagnostics, particularly in complex applications like battery management. By integrating AI models into embedded systems, the industry can achieve more accurate, cost-effective, and resource-efficient solutions, ultimately benefiting consumers with smarter and more reliable devices.

Key Takeaways

This webinar explores how AI‑based virtual sensors can be used to estimate signals that are difficult or costly to measure, such as battery state of charge (SOC) in Battery Management Systems. Using a practical example, the session demonstrates how AI models can be integrated into system‑level design and validated against performance, resource, and deployment constraints.

The workflow shows how to design, verify, compress, and deploy AI‑based virtual sensors to embedded processors within a single environment.

You will learn how to:

Integrate AI models into Simulink® for system ‑ level simulation and verification

Apply formal verification to assess neural network behavior

Optimize models for memory footprint and execution speed

Generate and profile library ‑ free C code for embedded deployment

Evaluate design tradeoffs across accuracy, performance, and deployment targets

Click ‘Watch Now’ to explore this webinar.