Application of Load Angle Torque Equation for Direct Torque Control of Permanent Magnet Synchronous Motor on ARM Embedded Platform
2025
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Advisor: Doç. Dr. Mehmet Polat
Abstract (EN)
In Permanent Magnet Synchronous Motors (PMSMs), torque ripple negatively impacts the control performance of motor drive systems and poses significant challenges in applications requiring high-precision torque output. Eliminating or mitigating these torque fluctuations is essential for improving the accuracy and reliability of PMSM based systems. In this regard, minimizing torque ripple and achieving a precise torque response are critically important for systems that demand high control fidelity. To address torque ripple in PMSMs, various factors have been investigated, including controller design, motor structural configuration, flux control strategies, and torque estimation equations. Among these approaches, particular emphasis has been placed on the torque estimation equation used in PMSM control, which typically involves multiple time-varying parameters. It has been observed that reducing the number of these parameters leads to a decrease in torque ripple and allows for more effective control of the fluctuations. Accordingly, a torque estimation equation has been proposed that depends solely on the load angle and incorporates only a single time-varying parameter. This formulation confines torque ripple to be a function of the load angle alone. Simulation studies comparing the proposed torque equation with two conventional models from the literature have been conducted, and the results confirm the validity and effectiveness of the proposed approach. Furthermore, experimental validation using a Hardware in-the-Loop (HIL) technique with the STM32F429I ARM-based control board has demonstrated the practical success of the proposed torque estimation model.
Author
Ebubekir Bozkurt
Institution
How to Cite
Ebubekir Bozkurt (Doctorate thesis). Application of Load Angle Torque Equation for Direct Torque Control of Permanent Magnet Synchronous Motor on ARM Embedded Platform, 2025, Fırat University.
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