Search

This article proposes a novel condition monitoring method for heatsink of traction inverter of urban rail train by detecting the change of temperature dynamic curves. Artificial neural network is used to predict the reference curves of healthy state under various working conditions, and the differences between temperature dynamic curves are extracted by one-way distance algorithm. This method is suitable for the condition monitoring of heatsink of urban rail train, because first it meets the diversity of operation conditions and nonthermal equilibrium state of traction inverter. Moreover, its implementation does not cause intrusion to the original system, and can realize online monitoring. Finally, the effectiveness is experimentally verified. [ABSTRACT FROM AUTHOR]

Gate-oxide degradation has been one of the critical reliability concerns of silicon carbide (SiC) metal–oxide–semiconductor-field-effect transistors (mosfets), which could be monitored through aging-sensitive parameters. In this article, an online gate-oxide degradation monitoring method for planar SiC mosfets is proposed by extracting gate charge time at a specific range of gate voltage. It is based on the findings that the input capacitances of planar SiC mosfets change significantly over gate-oxide degradation, which is theoretically analyzed and experimentally verified. The capacitance variations are converted into the gate charge time as the new aging-sensitive parameter. The new parameter measurement circuit is proposed and integrated into the gate driver module. The article results indicate that the new parameter varies noticeably with gate-oxide degradation and the difference of this parameter caused by junction temperature is much smaller than that caused by degradation. Besides, the parameter is immune to package degradation and load current. The condition monitoring method can be implemented online since the parameter is extracted during the off-state of SiC mosfet devices, which does not affect normal operation. The confirmatory experiment is carried out to verify the correctness of the proposed method. [ABSTRACT FROM AUTHOR]

In this article, an online condition monitoring (CM) method is proposed for the bond wire degradation of insulated-gate bipolar transistor (IGBT) modules in a single-phase or three-phase three-level neutral-point-clamped (3LNPC) dc–ac, ac–dc converter. The proposed method has the ability to detect the whole IGBTs in a 3LNPC converter, based on finding the idle on-state IGBTs under the specific load current direction and switching sequence of a leg. The detection time is short (0.2 ms) and the influence of online CM on load current can be completely neglected as long as the insertion areas for CM test are chosen reasonably. Meanwhile, an advanced bond wire CM module is designed to conduct the CM test. This module can generate and inject the current pulse trains into IGBT modules, with the high current for CM test and low current for temperature-sensitive electrical parameter measurement, and sample the collector–emitter on-state voltage (VCE ON) stably and precisely. Finally, the experimental work was carried out to verify the effectiveness of the proposed method and the practicality of the developed CM module. [ABSTRACT FROM AUTHOR]