High-Precision Estimation of SRM Rotor Position Based on Optimization of Prediction Current Error

To address the challenge that the accuracy of rotor position estimation in switched reluctance machines (SRMs) struggles to meet the requirements of high-performance control, this article proposes an optimization-based position estimation technique leveraging the mapping relationship between current prediction errors and rotor positions. By constructing polynomials for predicted current and rotor position using flux linkage information from the conducting phase, the method intelligently expands data samples and identifies the optimal estimated position through comparative analysis of predicted versus actual current deviations. Experimental results demonstrate that, compared to conventional nonconducting phase pulse injection-based approaches, the proposed method reduces the mean absolute value of error (MVE) ranging between 0.65$^\boldsymbol{\circ}$and 0.99$^\boldsymbol{\circ}$while exhibiting strong robustness.