Automatic Braking System for Micro Electric Vehicle Using Tsukamoto Fuzzy Logic

This research proposes the design of an Automatic Braking System (ABS) for Micro Electric Vehicles (MEVi) using the Tsukamoto Fuzzy Logic method to enhance driving safety through adaptive braking control. The system employs ultrasonic sensors to measure the distance to obstacles, with outputs in the form of braking pressure and speed, which are used to control a stepper motor actuator. Two microcontrollers, Teensy 4.1 and Arduino Nano, are utilized for data processing and actuator control, integrated via UART serial communication and Modbus RTU protocol. To ensure measurement reliability, the ultrasonic sensors were calibrated using a linear regression method, which improved their accuracy to 98%. Experimental results demonstrate that the system is capable of adjusting braking responses dynamically based on variations in vehicle speed and distance. At close range, the system applies a braking pressure exceeding 1200 units to prevent collisions, while at longer distances, the pressure is reduced by up to 66% to maintain vehicle stability. The use of Tsukamoto Fuzzy Logic enables crisp and responsive decision-making suitable for real-time conditions. These findings indicate that fuzzy-based ABS systems have strong potential for integration into electric vehicles, offering significant improvements in safety and operational efficiency.