Scholarlink

The control techniques for BLDC motors are highly varied and essential for precise and robust navigation of differential mobile robots. Among these methods, vector control with field orientation provides optimal performance. This work aims to integrate two BLDC motors and the motherboard, controlled by an STM32 microcontroller from an original hoverboard, to develop an experimental platform. This will allow us to perform various autonomous navigation tests with the resulting differential mobile robot. The challenge is to replace the original hoverboard motor control with a new system based on a Raspberry Pi 4 using the UART protocol. This new system must enable the control of the two BLDC motors, including vector control, and provide high performance for the mobile part of the robot. Additionally, implementing field-oriented control requires the acquisition of the currents and fluxes from the BLDC motors, which is ensured by the Hall effect sensors integrated into the Hoverboard. This new platform, equipped with lidar and 3D Kinect camera vision systems, will enable us to experiment with innovative visual localization and navigation methods for the differential mobile robot. The speed control results of the new platform and the acquisition of the BLDC motors stator currents were imported into MATLAB for visualization. The results demonstrate enhanced compliance with speed commands for both BLDC motors.

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Development of a Novel Differential Mobile Robot Platform Based on an Original Hoverboard and Experimental Validation of Field-Oriented Control (FOC) for BLDC Motors

  • 会议论文

  • 发表日期：

    2025年

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  • Yassine Rhib,
  • Nabila Rabbah,
  • Abdelwahed Touati

摘要

The control techniques for BLDC motors are highly varied and essential for precise and robust navigation of differential mobile robots. Among these methods, vector control with field orientation provides optimal performance. This work aims to integrate two BLDC motors and the motherboard, controlled by an STM32 microcontroller from an original hoverboard, to develop an experimental platform. This will allow us to perform various autonomous navigation tests with the resulting differential mobile robot. The challenge is to replace the original hoverboard motor control with a new system based on a Raspberry Pi 4 using the UART protocol. This new system must enable the control of the two BLDC motors, including vector control, and provide high performance for the mobile part of the robot. Additionally, implementing field-oriented control requires the acquisition of the currents and fluxes from the BLDC motors, which is ensured by the Hall effect sensors integrated into the Hoverboard. This new platform, equipped with lidar and 3D Kinect camera vision systems, will enable us to experiment with innovative visual localization and navigation methods for the differential mobile robot. The speed control results of the new platform and the acquisition of the BLDC motors stator currents were imported into MATLAB for visualization. The results demonstrate enhanced compliance with speed commands for both BLDC motors.