Orthogonal-Flux-Estimation and Enhanced PLL for Sensorless Control of Switched Reluctance Motors With Fault-Tolerant

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Authors: Zebin Yang, Zheng Zhang, Xiaodong Sun, Chao Sun
Cited by: 1
References: 35

Abstract

In order to reduce the cost of the sensor for switched reluctance motors (SRMs) and improve the accuracy of position estimation, a sensorless control strategy based on the orthogonal flux linkage and improved phase-locked loop (PLL) is proposed in this article, along with a fault-tolerant control scheme to ensure operational performance under single-phase fault conditions. The proposed control strategy is applied during the medium-high speed stage. First, the nonlinear rotor flux linkage containing position and speed information is expanded into a Fourier form. By using a dual second-order generalized integrator quadrature signal generator, the DC bias and high-order harmonics are eliminated, and a set of mutually orthogonal flux linkage signals is generated. Then, the differential of the motor speed is taken as the extended state variable of the extended state observer, the rotor estimated position and speed can be obtained by using the extended state observer-based phase-locked loop to process the orthogonal signals. Furthermore, a fault-tolerant control strategy is proposed to enhance the performance of this control strategy in the case of single-phase fault. Finally, a comparative experiment is conducted on a six-phase 12/10 SRM against the traditional method. The experimental results show that this control strategy not only validates the superiority of the proposed sensorless control strategy, but also demonstrates its satisfactory estimation performance under single-fault conditions.

Fields of Study & Subjects

Sensorless Control of Electric Motors Electric Motor Design and Analysis Magnetic Field Sensors Techniques

Publication details

Journal / source
IEEE Transactions on Industrial Electronics
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
73
Issue
8
Pages
11176–11186
Publication date
3 March 2026