Improved Feature-Position-Based Sensorless Control Scheme for SRM Drives Based on Nonlinear State Observer at Medium and High Speeds
Dianxun Xiao, Jin Ye, Gaoliang Fang, Zekun Xia, Xueqing Wang, Ali Emadi
Abstract
The article proposes a nonlinear state observer (NSO) for robust position-sensorless control of switched reluctance motor (SRM) drives over medium- and high-speed range. A classical reference flux-linkage method is adopted to capture a feature position of the SRM, which avoids the use of 3-D magnetic characteristics and has better universality. However, the estimation accuracy of this method would be deteriorated due to flux-linkage errors. To ease the problem, the NSO is developed to enhance the robustness against flux-linkage distortions for more accurate position and speed estimation. This observer can first reconstruct complete position information from a low-resolution feature position. The adverse impact of flux-linkage errors on position estimation is then investigated through a novel small-signal approximation and suppressed by an augmented state estimator. Afterward, a parameter design scheme is given to ensure the observer's stability and improve the capability in distortion suppression. To baseline the performance, comparative experimental validation between the proposed NSO and a widely used linear prediction method is conducted on a 12/8 SRM setup. The results show that the proposed strategy can improve the overall position-sensorless control performance in both the steady and transient states.