The enhancement of edge computing with AI-enabled functionality promises to revolutionize the cloud and Internet of Things (IoT). Companies like Texas Instruments are beginning to offer advanced solutions that bring AI to the edge, like the C2000 series of real-time MCUs.
For example, in motion-control applications where you have motors that are spinning, real-time detection can help determine if there's a fault, or a bearing is performing badly, or other problems exist with the system. Such a system can also aid in predictive maintenance and fault recovery.
Devices in the C2000 family integrate an edge AI accelerator to enable motor control while also detecting sensing inputs to see if there's a fault in the motor and how it's doing. The device can sense any change in the parameters to detect whether there's a fault in the motor or motors involved.
C2000 MCUs offer low-latency, real-time control for a range of automotive and industrial applications. When used with wide-bandgap GaN and SiC power devices, they can enable higher switching frequencies, increase power density, and improve accuracy and efficiency.These are paired with a software ecosystem that includes advanced security and functional-safety features, especially useful in onboard charging and DC-DC conversion, energy infrastructure, motor-drive and body-control applications.
The MCUs can also be used in other demanding applications, such as identifying and de-energizing dangerous arcs. They achieve greater than 98% detection accuracy on bearing and load imbalance faults with on-chip learning options for anomaly detection. In this video, Texas Instruments' Vivek Singhal explains two demos that highlight these capabilities.
