power components
Qorvo Machine Learning in Power Management Systems

Qorvo Machine Learning in Power Management Systems

Applying machine learning to an application such as battery management is a multi-dimensional problem, with the goal of a) adding charge as rapidly, safely, and efficiently as possible, while b) controlling discharge with minimum stress.

MCU-based machine learning, known as “tiny ML,” is an emerging technology that offers promising enhancements for power management applications. Examples include fault and anomaly detection for improved safety and reliability, virtual sensing of system parameters for reduced system cost, and new predictive maintenance applications for increased system efficiency and reliability. Qorvo’s intelligent power management SoCs include ARM Cortex MCUs and an array of analog sensors from which the tiny ML algorithms can learn and improve performance. Qorvo offers evaluation kits that support both data collection and firmware testing, which, when combined with 3rd party AutoML tools, provide the necessary elements for ML algorithm development for today’s SoCs

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