Direct Torque Control of BLDC Motors with Low Torque Ripple Implementation

Direct Torque Control (DTC) of Brushless DC (BLDC) motors serves as an effective strategy for achieving precise torque and speed regulation. Traditional DTC implementations for BLDC motors often exhibit significant torque ripple, which can adversely affect performance in sensitive applications. To mitigate this challenge, researchers have developed advanced control techniques that incorporate torque ripple reduction mechanisms. Predictive torque control algorithms utilize mathematical models to forecast motor torque and stator flux values for upcoming switching periods, enabling preemptive adjustments through code implementations that calculate optimal voltage vector selection. Fuzzy logic control systems employ rule-based inference mechanisms to dynamically adapt control parameters based on real-time torque error analysis, typically implemented using membership functions and defuzzification algorithms in the control code. These enhanced DTC methodologies have demonstrated substantial reductions in torque ripple while improving overall system performance across diverse applications including electric vehicle propulsion systems, robotic motion control, and industrial automation platforms.