We develop software that generates real-time embedded digital twin solutions for model predictive control and diagnostics of electromechanical systems, enhancing performance, longevity, and reliability.In essence, our toolchain creates a precise digital replica of a physical device, such as an electric motor or generator, in order to accuratelymodel the electrodynamic and thermodynamic behavior of the system across a wide range of operating conditions.We then apply our proprietary mathematical approach to exponentially reduce the computational complexity of this model—so much so, in fact, that our digital twin can be integrated into the device itself to compute in real-time, “on-chip,” as part of an amazingly fast and accurate firmware solution.By accurately predicting temperatures and other critical system parameters thousands of times per second, our Digital Twin On-Chip solutions not only provide unprecedented insight for real-time control techniques to enhance system performance, but also pave the way for data-as-a-service capabilities such as predictive maintenance, monitoring of component aging, and anomaly detection.

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People (3)

Francesco Toso

Andrea Favato

Arianna Muratore

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