BLDC motor driver design for electric vehicles

The main objective of this thesis is to enable direct drive speed control of electric vehicles by utilizing an external rotor Hub Brushless Direct Current (BLDC) motor, which is controlled using the 6- step method through a microcontroller and an area-effective (Hall effect) sensor. This control is achieved by referencing the isolated analog signal input in the range of 0-10 volts, allowing for precise speed control of the electric vehicles. The study will emphasize the safety advantages of isolated analog input and minimize the margin of error caused by the tolerance value of resistors in the analog input via a learning algorithm. This algorithm entails the learning of maximum and minimum values by the card upon initial operation and recalculating the output signal equation for every distinct card. As a result, hardware discrepancies are disregarded, and all cards provide equivalent responses at the same voltage level. This approach enables sharper and more stable speed control. The project aims to design a simple, efficient, economical, quick, and secure motor control system using Switched-Mode Power Supply (SMPS) and IPM (Intelligent Power Module). To reach this goal, an in-depth literature review will be conducted initially to determine the current state of the field by examining similar studies. Following this, a microcontroller-based control system will be designed and implemented on the printed circuit board. In conclusion, the performance of the designed printed circuit board control system will be evaluated through experiments and simulations. The results obtained aim to provide a practical application in the field of Brushless Direct Current (BLDC) motor control while serving as a fundamental reference for similar applications. Keywords: Analog Isolation, BLDC (Brushless Direct Current), IPM (Intelligent Power Module), Learning Algorithms, Resistance Tolerance Analysis, Speed Control, STM32