Optimization of BLDC Motor Controller for Enhancing Battery Performance

Brushless DC (BLDC) motors are extensively used in electric two- and threewheelers due to their superior electrical and mechanical performance, making them ideal for lightweight electric vehicles. The speed control of BLDC motors can be broadly classified into scalar and vector control techniques. Among scalar approaches, trapezoidal control is the simplest, where motor windings are sequentially energized. However, such methods tend to be less efficient and exhibit reduced performance at higher speeds. In contrast, Field Oriented Control (FOC), a vector-based technique, generates three-phase sinusoidal signals whose frequency and amplitude can be precisely controlled. This method offers improved torque and speed regulation, higher efficiency, faster dynamic response and a wider operational speed range. This paper focuses on optimizing BLDC motor speed control to enhance battery utilization. MATLAB simulations are conducted to evaluate the proposed optimization technique and the system’s performance is assessed through the battery’s State of Charge (SoC). Particle Swarm Optimization (PSO) is employed to fine-tune the controller gain parameters for improving the system efficiency.