Fault Diagnosis for Power Converter in SRM Drives Based on Current Prediction

Abstract

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 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> th 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 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> -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.