Abstract:

Electric vehicles play a crucial role in reducing greenhouse gas emissions, improving air quality, increasing energy efficiency and transitioning to renewable energy sources. They also contribute to energy independence, promote innovation and offer significant economic benefits.

At UNAM's School of Engineering, the development of an educational prototype of an electric vehicle as part of the Control and Robotics Engineering program is essential for the comprehensive training of students. This project not only drives technological advancement and the promotion of sustainability, but also strengthens the connection with industry and society, preparing students to face future challenges and contribute significantly to engineering.

The methodology used for the development of the educational prototype began with an exhaustive diagnosis of the TETRIX® Robot and its components. The mechanical structure, electric motors, and battery of the original model were reused, and higher-capacity batteries were opted for. Advanced motor controllers were incorporated using Raspberry Pi 4 microcomputers, which allow remote communication via SSH protocol. Infrared sensors and a camera controlled by Raspberry Pi were installed to improve vehicle safety and navigation. In addition, educational software and intuitive applications were developed to facilitate student interaction and programming of the prototype.

Re-engineering of the prototype has significantly improved the efficiency, functionality and robustness of the design. Improvements include greater autonomy and safety, with the incorporation of infrared sensors and a camera for impact protection.

The educational software and mobile applications developed have provided practical tools for students to control and program the vehicle, as well as to analyze data in real time. Extensive testing has confirmed that the prototype meets the established performance and functionality.

Tests have shown that the sensors perform well in various lighting conditions, with an optimal detection distance of up to 45 cm. The camera's image transmission is high-definition, and the battery provides a proper usage time of at least 24 hours. The speed of the electric motors can be precisely adjusted by PWM signals. The graphical navigation interface is intuitive and accessible to all users.

For autonomous navigation, algorithms have been implemented to allow the robot to follow fixed trajectories and avoid obstacles, using a gyroscope to define precise rotations. Tests showed that the trajectories hold well on smooth, porosity-free soils, and accurate calibration was required to ensure rotations with defined angles. The implementation of discrete low-pass filters has improved the accuracy of the gyroscope and other sensors. Obstacle avoidance is effective on straight trajectories, and the incorporation of emerging technologies such as computer vision is suggested to improve this capability.

Keywords:

Electric Vehicle Prototype, Autonomous Navigation, Educational software, Robot Re-engineering.