Review on improving Accuracy in Position Estimation For SynrmSensor Less Control Systems By Optimizing And Mitigating Dead-Time Harmonic

Abstract

This review investigates recent advancements in mitigating dead-time harmonic distortion and rotor position estimation errors in the sensorless control of Synchronous Reluctance Motors (SynRMs). The objective of this study is to analyze how various control and compensation techniques improve current waveform linearity, torque smoothness, and estimation accuracy under inverter non-idealities. The methodology involves a comparative evaluation of recent research focusing on dead-time compensation algorithms, optimized PWM schemes, adaptive observers, and AI-based estimation approaches. These studies were systematically reviewed to assess their experimental validation, implementation feasibility, and performance improvements across different motor configurations. The results reveal that adaptive and AI-driven compensation methods effectively minimize harmonic distortion and enhance sensorless estimation reliability, especially in low-speed regions where back-EMF signals are weak. However, limitations persist in achieving robust real-time adaptability and scalability for high-power applications. The review concludes that integrating intelligent hybrid control architectures with hardware validation can lead to more efficient, accurate, and reliable SynRM drives, paving the way for the next generation of sustainable industrial motor systems.