Parameter Estimation and Comparative Analysis of Control Design Techniques for BLDC Hub Motor

Brushless DC (BLDC) motors have become the optimal choice for high-precision controller implementation in industrial applications. This paper presents a detailed analysis of a hub BLDC motor used in low power electric vehicles right from parameter estimation to the implementation of speed control techniques. The parameter estimation is followed by the development of the mathematical model of the BLDC motor. The conventional PID technique and the genetic algorithm-based tuning are applied to the mathematical model. Further physical model of the motor is constructed and simulated for broadly 3 control methods: Conventional PID, Genetic algorithm, and self-tuning Fuzzy logic method. The purpose of the research is to provide a comparative analysis of these control strategies and to identify the optimal one for speed-control of the BLDC hub motor. Results show that the proposed, adaptive Fuzzy logic technique is the best control design for practical implementation.