With the emergence of technology capable of analyzing motor status in real time using AI, it is expected that the efficiency of motor control and predictive maintenance can be dramatically improved.

STMicroelectronics (hereinafter ST) announced on the 16th that it has released the 'FP-IND-MCAI1 Feature Pack,' an AI-based software that utilizes machine learning models to automatically identify the normal, high-vibration, and unstable states of a motor.

ST's new software can be installed directly on the EVLSPIN32G4-ACT evaluation board, enabling designers to easily manage complex workflows and tools to implement smart features.

It includes a sample application for driving a low-voltage 3-phase brushless motor using FOC (Field-Oriented Control), HAL, a dedicated board driver, and a machine learning solution.

Thanks to pre-configured ML models, users can quickly diagnose the condition of the motor and respond to various environments by adding customized classes.

EVLSPIN32G4-ACT drives a 3-phase brushless DC motor up to 250W and can enhance status monitoring by linking with a vibration detection module (STEVAL-C34KAT1, STWIN.box, etc.).

motor parameters through the STM32 Motor Control Software Development Kit (MCSDK) You can configure and control it, and you can also directly customize machine learning models using NanoEdge™ AI Studio.

In terms of hardware, the EVLSPIN32G4-ACT is equipped with an STSPIN32G4 motor drive SiP (System-in-Package), making it suitable for use as a reference design.

The 9mm x 9mm SiP integrates an Arm® Cortex®-M4 microcontroller, a half-bridge gate driver, bootstrap diodes, and protection circuits.

It is equipped with various functions such as MOSFET power stage, current sensing amplifier, and temperature sensor, and supports FOC or 6-level control, 3-shunt or single-shunt current sensing, and speed and position feedback through a digital Hall sensor and an incremental orthogonal encoder.

The FP-IND-MCAI1 feature pack can be downloaded for free from the official ST website, and the EVLSPIN32G4-ACT evaluation board is available for purchase from official distributors and eStores starting at $178.80.

At Embedded World 2026, held in Nuremberg, Germany last March, ST showcased a demo of motor control and predictive maintenance utilizing AI-embedded drivers and unveiled various solutions applicable to industrial sites. This new product is expected to offer new options to companies and developers seeking automation in motor control and innovation in maintenance.