Optimizing BLDC Motor Design: Practical Insights and Decision Tree Methodology for Enhanced Performance

Brushless Direct Current (BLDC) motors are essential for their efficiency and performance across various applications. Optimizing their design involves analyzing parameters such as lamination stack length, air gap, slot depth, insulation, slot number, and slot opening. This study uses Finite Element Analysis (FEA) and Steady State D-Q analysis with MOTORXP software to evaluate these parameters’ impacts on flux distribution, torque, and efficiency. The paper proposes a comprehensive empirical evaluation framework and a decision tree methodology for optimizing BLDC motor designs. These contributions offer detailed parameter analysis, systematic evaluation, and practical insights, enhancing motor design for improved performance and efficiency.