The new family has a range of peripheral functions and AI-based failure detection that assist the MCUs in motor control and predictive maintenance applications. The four new RA6T1 Group MCUs are the latest members of Renesas’ expanding Arm-based RA MCU family.
“As home appliances and building and industrial automation equipment become smarter and more complex, manufacturers are grappling with rising BOM costs to support increasing motor performance demands,” said Roger Wendelken, Senior Vice President of Renesas’ IoT and Infrastructure Business Unit. “The RA6T1 MCUs combine the superior performance and flexibility of the Arm-based RA Family with Renesas’ long-standing motor control expertise. In addition, with the emergence of AI-based needs, Renesas is excited to complement Google’s TensorFlow Lite supported platforms with the RA6T1 motor control and predictive maintenance solution.”
“AI and machine learning are taking predictive maintenance to the next level as the industry advances toward Maintenance 4.0. We are excited to join forces with Renesas and accelerate the adoption of smart home and IIoT applications,” said Ian Nappier, Product Manager at Google. “Integrating our open-source TensorFlow AI framework with Renesas’ powerful RA6T1 MCUs brings breakthrough intelligence to motor control equipment.”
The new RA6T1 32-bit MCUs are based on Arm’s Cortex-M4 core operating at 120 MHz. The MCUs offer a range of peripherals that are optimized for high performance and precision motor control. Integrated peripherals with high-speed analog reduce the BOM cost and boost motor control performance. A single RA6T1 MCU can control two BLDC motors at the same time. The Google TensorFlow Lite Micro framework for TinyML applications provides the RA6T1 MCUs with enhanced failure detection. This feature offers an intelligent and cost-effective sensorless motor system for predictive maintenance. The TensorFlow AI framework can detect potentially detrimental anomalies in motor systems quickly and accurately to assist in the improvement of predictive maintenance processes and the reduction of maintenance costs.
The new Renesas Solution Starter Kit (RSSK) helps in the development