The insulated gate bipolar transformer (IGBT) has been widely used in power electrical system such as wind power converter and drive converter. However, the high load and capricious working environment make IGBT become the most vulnerable component in the electrical system. In this paper, a method based on probabilistic forecasting with auto-regressive recurrent networks (DeepAR) is proposed to predict the remaining useful life (RUL) of IGBT. Firstly, the transient data of the collector-emitter voltage signal are acquired when IGBT is turned off. Then, the different characteristics are extracted from transient data and the features that can represent the health state of IGBT best are chosen as the input of the DeepAR model to predict the remaining life of IGBT. Experiment results show that the log-log ratio of transient data can be an accurate precursor to predict RUL, and compared with other similar series predict models such as Auto-Regressive Integrated Moving Average (ARIMA) and Simple Exponential Smoothing (SES), DeepAR can get higher accuracy.

This paper presents a fixed-switching-frequency model predictive current controller using multiplexed current sensor for switched reluctance machine (SRM) drives. The converter was modified to distinguish currents from simultaneously excited phases during the sampling period. The only current sensor installed in the converter was time division multiplexing for phase current sampling. During the commutation stage, the control steps of adjacent phases were shifted so that sampling time was staggered. The maximum and minimum duty ratio of pulse width modulation (PWM) was limited to keep enough sampling time for analog-to-digital (A/D) conversion. Current sensor multiplexing was realized without complex adjustment of either driver circuit nor control algorithms, while it helps to reduce the cost and errors introduced in current sampling due to inconsistency between sensors. The proposed controller is validated by both simulation and experimental results with a 1.5 kW three-phase 12/8 SRM. Satisfied current sampling is received with little difference compared with independent phase current sensors for each phase. The proposed controller tracks the reference current profile as accurately as the model predictive current controller with independent phase current sensors, while having minor tracking errors compared with a hysteresis current controller.