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An Aging-Degree Evaluation Method for IGBT Bond Wire with Online Multivariate Monitoring

Author

Listed:
  • Zilang Hu

    (National Rail Transportation Electrification and Automation Engineering Technology Research Center, Southwest Jiaotong University, Chengdu 611756, China)

  • Xinglai Ge

    (National Rail Transportation Electrification and Automation Engineering Technology Research Center, Southwest Jiaotong University, Chengdu 611756, China)

  • Dong Xie

    (National Rail Transportation Electrification and Automation Engineering Technology Research Center, Southwest Jiaotong University, Chengdu 611756, China)

  • Yichi Zhang

    (National Rail Transportation Electrification and Automation Engineering Technology Research Center, Southwest Jiaotong University, Chengdu 611756, China)

  • Bo Yao

    (National Rail Transportation Electrification and Automation Engineering Technology Research Center, Southwest Jiaotong University, Chengdu 611756, China)

  • Jian Dai

    (National Rail Transportation Electrification and Automation Engineering Technology Research Center, Southwest Jiaotong University, Chengdu 611756, China)

  • Fengbo Yang

    (National Rail Transportation Electrification and Automation Engineering Technology Research Center, Southwest Jiaotong University, Chengdu 611756, China)

Abstract

The aging fracture of bonding wire is one of the main reasons for failure of insulated gate bipolar transistor (IGBT). This paper proposes an online monitoring method for IGBT bonding wire aging that does not interfere with the normal operation of the IGBT module. A quantitative analysis of aging degree was first performed, and the results of multivariate and univariate monitoring were compared. Based on the relationship between the monitoring parameters and the aging of the IGBT bonding wire, gradual damage of the IGBT bond wire was implemented to simulate aging failure and obtain the aging data. Moreover, the change of junction temperature was considered to regulate monitoring parameters. Then, the aging degree was evaluated by an artificial neural network (ANN) algorithm. The experimental results showed the effectiveness of the proposed method.

Suggested Citation

  • Zilang Hu & Xinglai Ge & Dong Xie & Yichi Zhang & Bo Yao & Jian Dai & Fengbo Yang, 2019. "An Aging-Degree Evaluation Method for IGBT Bond Wire with Online Multivariate Monitoring," Energies, MDPI, vol. 12(20), pages 1-18, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3962-:d:277924
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    References listed on IDEAS

    as
    1. Erik E. Kostandyan & John D. Sørensen, 2011. "Reliability Assessment of Solder Joints in Power Electronic Modules by Crack Damage Model for Wind Turbine Applications," Energies, MDPI, vol. 4(12), pages 1-13, December.
    2. Qingyi Kong & Mingxing Du & Ziwei Ouyang & Kexin Wei & William Gerard Hurley, 2019. "A Method to Monitor IGBT Module Bond Wire Failure Using On-State Voltage Separation Strategy," Energies, MDPI, vol. 12(9), pages 1-13, May.
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    Cited by:

    1. Chao Zhou & Bing Gao & Haiyue Yang & Xudong Zhang & Jiaqi Liu & Lingling Li, 2022. "Junction Temperature Prediction of Insulated-Gate Bipolar Transistors in Wind Power Systems Based on an Improved Honey Badger Algorithm," Energies, MDPI, vol. 15(19), pages 1-19, October.
    2. Faisal Wani & Udai Shipurkar & Jianning Dong & Henk Polinder, 2021. "Thermal Cycling in Converter IGBT Modules with Different Cooling Systems in Pitch- and Active Stall-Controlled Tidal Turbines," Energies, MDPI, vol. 14(20), pages 1-25, October.

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