Open AccessOnline sensorless fault diagnosis and remediation strategies selection of transistors for power converter in SRD
Author(s) -
Xu Shuai,
Chen Hao,
Dong Feng,
Cui Sihang
Publication year - 2019
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 97
eISSN - 1751-8679
pISSN - 1751-8660
DOI - 10.1049/iet-epa.2019.0087
Subject(s) - reliability (semiconductor) , fault (geology) , converters , engineering , rss , computer science , power (physics) , control theory (sociology) , electronic engineering , voltage , reliability engineering , electrical engineering , control (management) , physics , quantum mechanics , artificial intelligence , seismology , geology , operating system
The fault diagnosis methods and remediation strategies (RSs) are critical for high‐reliability operation of power converters in switched reluctance motor drive (SRD). This study presents an online sensorless fault diagnosis method and effectively selects the RSs from the reliability view. To begin with, the equations of neutral voltage are derived for each phase leg in popular asymmetric half‐bridge converter under normal and faulty operation conditions. Next, the diagnosis criterion is proposed with the combination of drive signals and neutral voltage signatures. Besides, the low‐cost circuits are designed to save the diagnosis cost, especially for the control strategies without any current or voltage sensor. Moreover, the diagnosis time can be decreased to 7 µs and not affected by the speed, load torque, control strategies and topologies. Moreover, the proposed method can also identify the multiple faults of transistors. In addition, to further enhance the reliability of power converter and then for SRD, the reliability‐oriented selection of RSs is carried out by means of the dynamic Markov model. Finally, the experiments of fault diagnosis and thermal stress measurement are conducted to confirm the effectiveness of the proposed diagnosis method and RSs selection.