Search

This article proposes an online diagnosis scheme for transistor faults of asymmetric half-bridge converter (AHBC) in switched reluctance motor (SRM) drives. In order to extract more information from the phase current to identify faults, based on the conventional current measurement method, two novel current measurement methods are presented by reconstructing current sensors. According to the novel current measurement methods, a current prediction method is raised. The phase current at the kth sampling time is available so that the estimated current can be calculated. The fault can be detected and located by analyzing the given and actual switching states, which are deduced by comparing the measured and estimated currents. Compared with existing methods, the proposed scheme can be applied to diagnosis of multiple faults in n-phase AHBC, which can operate at various control strategies and chopping modes. With a single current sensor in each phase, the scheme will not increase the cost and complexity of the SRM drive. Furthermore, the scheme does not require complicated computation, making it easy to implement online. The experimental results confirm the effectiveness and flexibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

A novel method to suppress the force ripple of switched reluctance linear motors (SRLMs) based on predictive-fuzzy control is proposed in this article. Generally, the force ripple mainly occurs in the commutation area, resulting from the dropping force of the outgoing phase that cannot match the rising force of the incoming phase. The force distribution function (FDF) is a suitable method for controlling the forces of the outgoing phase and incoming forces during the commutation area. However, the controller calculation takes time and the motor shows inductive behavior, so the control signal, which is the reference current in FDF, always lags the reference force, which weakens the effect of the FDF control. Considering this problem, a method of predictive-fuzzy control is proposed in this article. The current can be controlled in advance by predicting the force, which reduces the appearance of the negative electromagnetic force, which is beneficial to improving the efficiency of the motor, and the mutual inductance is also considered in the predictive model. Additionally, a fuzzy controller is employed, and adaptive parameters of the control system are adopted. To validate the proposed control system, experimental verification is performed on a 500 W 6/4 double-sided SRLM, showing that the proposed method has a better force ripple suppression performance than the FDF control. [ABSTRACT FROM AUTHOR]

This paper mainly takes a 6/4 switched reluctance motor (SRM) as an example to analyze the temperature of the motor. In order to establish the equivalent thermal circuit model (ETCM) conveniently, the mechanical structure of the motor is simplified to a certain extent, and the characteristic nodes are divided. Then the heat transfer process in the rotor region, the stator region and the whole motor during the operation of the motor is analyzed, and the ETCM of those regions are established respectively. This method of establishing ETCM is also applicable to superconducting motors. Based on the basic principles of heat transfer, the calculation method of thermal resistance in each ETCM is given in this paper. Then, the three-dimensional (3-D) finite element (FE) temperature field model of the motor is built and compared with the ETCM. Finally, the accuracy of the ETCM is verified by experiments. [ABSTRACT FROM AUTHOR]