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IGBT Remaining Useful Life Prediction Based on Particle Filter With Fusing Precursor

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The remaining useful life (RUL) prediction is essential for the IGBT module when setting a reasonable maintenance schedule and improving IGBT reliability by design. In this article, an RUL prediction… Click to show full abstract

The remaining useful life (RUL) prediction is essential for the IGBT module when setting a reasonable maintenance schedule and improving IGBT reliability by design. In this article, an RUL prediction method is proposed based on the particle filter (P.F.) algorithm with a multi-parameter precursor developed from the IGBT aging data. By fusing the junction temperature ( $T_{j}$ ) and collector-emitter on-voltage( $V_{CE(on)})$ , a new fault precursor is established to monitor IGBTs’ condition. A simplified aging model of the precursor is also developed based on a two-stage fitting. After input the historical aging data of the selected IGBT module, the RUL of IGBT can be predicted by the proposed fault precursor based on P.F. algorithm. According to the aging data collected from accelerated aging experiments, the performance of RUL prediction using the fusing precursor is superior to those with the single parameter precursor.

Keywords: useful life; igbt; precursor; prediction; based particle; remaining useful

Journal Title: IEEE Access
Year Published: 2020

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