Results in Engineering (Mar 2025)
Design and implementation of electric vehicle with autonomous motion and steering control system using single board computer and sensors
Abstract
Autonomous motion and steering systems are crucial in electric vehicle (EV) technologies, enabling enhanced safety, efficiency, and user convenience. However, the integration of modern sensors and controllers and actuator mechanisms remains a significant challenge to achieving autonomous functionality in EVs. This study presents the design, integration, and implementation of an EV control system that operates in both manual and autonomous modes. In manual mode, the driver maintains complete control via the ignition key, emergency checks, and mechanisms for selecting direction and speed. Transitioning to autonomous mode involves integrating an autonomous vehicle electronic control unit (AV-ECU), which manages the existing electric vehicle electronic control unit (EV-ECU) as a subordinate unit. A Raspberry Pi 5 system-on-chip (SoC) serves as the master controller, coordinating motion and steering commands. In autonomous mode, the system leverages a range of sensors and actuators for navigation and control. The LIDAR-Lite v3HP sensor facilitates obstacle detection and distance measurement for real-time speed adjustments. A rotary encoder tracks steering angle and rotation direction, ensuring accurate maneuverability. Speed control is achieved through pulse width modulation (PWM) signals that adjust power to the motor, allowing for speeds varying from 0 to 40 km/h. Responsive steering control is provided by a worm gear motor system, managed by a motor driver that interfaces with the single-board computer. The system's effectiveness was validated in a controlled campus environment, where it successfully enabled basic autonomous transportation. The incorporation of advanced sensors, electronic control units, actuators, and real-time data collection demonstrated the practical application of autonomous driving technologies, emphasizing the system's safety, efficiency, and potential for implementation in real-world scenarios.
