Arduino Nano Motor Carrier [ABX00041] - Add-on for Nano 33 IoT Board, Motor Control with 4 MP6522 Motor Drivers, ATSAMD11 Arm Cortex-M0+ (48MHz)

Original Arduino ABX00041 Arduino ABX00041 Accessory Nano Motor Carrier Nano Atmel SAMD21 Durable and Robust

• Enhanced Motor Control: The Arduino Nano Motor Carrier [ABX00041] is a powerful add-on board designed to work seamlessly with the Arduino Nano 33 IoT. It allows users to easily control up to four DC motors using the MP6522 motor driver ICs, making it ideal for robotics, automation, and IoT applications that require precise motor control.
• Powerful ATSAMD11 Processor: At the heart of the motor carrier board is the ATSAMD11 microcontroller, an Arm Cortex-M0+ core running at 48 MHz. This low-power, high-efficiency processor ensures real-time motor control and fast response times for your motor-driven projects, without compromising on performance or energy usage.
• Advanced Motor Driver Technology: The carrier features four MP6522 H-Bridge motor driver ICs capable of driving DC motors with up to 2.5A continuous current per motor, supporting a wide input voltage range (4.5V to 36V). This provides flexibility in selecting motors for various applications, from small robotics to more power-hungry systems.
• Easy Integration & Compatibility: Compatible with the Arduino IDE, the Nano Motor Carrier integrates seamlessly with the Arduino Nano 33 IoT board for easy setup and programming. The board offers standard pin headers for easy wiring and fast prototyping. Its compact design is ideal for embedded systems, robotics, and IoT projects that require both motor control and wireless communication.
• Versatile & Reliable Design: Built with durability in mind, the Nano Motor Carrier is designed for long-term reliability in demanding environments. It features overcurrent and thermal protection to safeguard both the motor driver circuits and connected motors, ensuring stable operation in a variety of conditions. The onboard motor feedback pins allow for monitoring and fine-tuning motor performance in real-time.