کنفرانس بین المللی ماشین و محرکه های الکتریکی

صفحه اصلی / The 3rd International Conference on Electrical Machines and Drives

Sensorless Control of Synchronous Reluctance Motors Based on Newton-Raphson Iteration Algorithm

نویسندگان :

Behnam Nikmaram¹ Mahdi S. Mousavi² Zahra Khalaji³ S. Alireza Davari⁴ Jose Rodriguez⁵ Mehdi Fazeli⁶

1- Electrical Machines Research Group, Niroo Research Institute, Tehran, Iran 2- Faculty of Engineering, Universidad San Sebastian, Santiago, Chile 3- Faculty of Technical and Engineering, Raja University, Qazvin, Iran 4- Department of Electrical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran 5- Faculty of Engineering, Universidad San Sebastian, Santiago, Chile 6- Department of Electrical Converters and Power Systems, IRIEE, ACECR, Tehran, Iran

کلمات کلیدی :

Synchronous reluctance motors،SynRM،Sensorless control،Phase-locked loop،PLL،Newton-Raphson iteration،Model predictive control،FCS-MPC

چکیده :

In this paper, a position estimation algorithm is proposed for sensorless control of synchronous reluctance motors (SynRMs) using the Newton function and a closed-loop flux model. The proposed method is a phase-locked loop (PLL) technique, in which the classic proportional-integral (PI) controller is replaced by a Newton-Raphson (NR) iteration algorithm. Hence, the problem of designing PI coefficients is resolved. The active flux concept is utilized as the Newton function. To obtain the active flux, a closed-loop flux model is presented using nonlinear feedback. This methodology compensates for uncertainties such as parameter mismatch, DC offsets, and inaccurate sensor gain errors to ensure the precise estimation of the position in medium and high-speed ranges. The NR-based PLL is converged only in three iterations. Therefore, the dynamic response of the proposed method is faster than using a classic PI controller. The proposed method is validated through MATLAB-Simulink simulations and experimental tests. The results show the fast and robust performance of the position estimation in various test conditions.