Power cycling test of transfer molded IGBT modules by advanced power cycler under different junction temperature swings

Choi, Ui-Min; Jørgensen, Solvejg; Iannuzzo, Francesco; Blaabjerg, Frede

doi:10.1016/j.microrel.2018.07.002

Cited by 9 publications

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Weibull distribution is chosen as an example as it is one of the most widely used distributions to represent the wear-out failure of power components in power electronics industry, especially for the lifetime model obtained from power cycling. This can also be observed in following power cycling reports [38]- [41]. The distribution can therefore be fitted by the Weibull probability density function (pdf ):…”

Section: B End-of-life Distribution Analysismentioning

confidence: 68%

Monte Carlo-Based Reliability Estimation Methods for Power Devices in Power Electronics Systems

Novak¹,

Sangwongwanich²,

Blaabjerg³

2021

IEEE Open J. Power Electron.

Self Cite

View full text Add to dashboard Cite

Monte Carlo simulation has been widely used for reliability assessment of power electronic systems. In this approach, multiple simulations are carried out during the lifetime estimation of the components in power converter, e.g., power devices, where the parameter variations are considered. In the previous mission-profile based reliability assessment methods, the dynamic thermal stress profiles are usually converted into a set of static parameters. However, this simplification may introduce a certain uncertainty during the reliability assessment, since the static parameters may not be able to accurately represent the thermal stress under highly dynamic conditions. Moreover, the previous research did not take into account the correlation between the method of introducing the parameter variation and the required number of Monte Carlo simulations. This can significantly affect both the accuracy and computation burden of the Monte Carlo simulation. To address this issue, an indepth analysis of Monte Carlo simulation applied to reliability assessment of power devices in power electronic systems is provided in this paper. Two additional Monte Carlo simulation approaches based on semi-dynamic and dynamic parameters are proposed, and their reliability evaluation results are compared with the traditional static parameter method. It is demonstrated in a case study of photovoltaic (PV) inverter application that the reliability of power converter can be overestimated up to 30% when using the static parameters.

show abstract

Section: B End-of-life Distribution Analysismentioning

confidence: 68%

Monte Carlo-Based Reliability Estimation Methods for Power Devices in Power Electronics Systems

Novak¹,

Sangwongwanich²,

Blaabjerg³

2021

IEEE Open J. Power Electron.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The criteria for reaching EOL involve a 20% increase in forward voltage (V f , V CE , or V DS ), thermal resistance (R th ), or temperature fluctuation ∆T, each compared to their initial values [57,59]. In other research, a 5% to 20% increase in V CE(ON) has been used as an IGBT module's EOL criterion [60], with the number of cycles leading up to these periods being tallied for a lifetime. Although this parameter is commonly used in previous studies, one investigation demonstrated that using a 5% V CE(on) increase as the EOL criterion does not accurately reflect the number of cycles to failure, as the IGBT under examination could still function for an additional 600k cycles after surpassing the 5% increase in V CE [61].…”

Section: Power Cycling Test Setupmentioning

confidence: 99%

Optimizing Insulated-Gate Bipolar Transistors’ Lifetime Estimation: A Critical Evaluation of Lifetime Model Adjustments Based on Power Cycling Tests

Alavi,

De Ceuninck,

Daenen

2024

Energies

View full text Add to dashboard Cite

This paper presents a detailed refinement and validation of two well-known lifetime prediction models for IGBTs, namely CIPS08 and SKiM63, using experimental power cycling test data. This study focuses on adapting these models to reflect the operational conditions and degradation patterns to more accurately fit different IGBT types and applications. Key modifications include recalibrating the scale factor and temperature coefficients in the SKiM63 model and refining the CIPS08 model coefficients (β1 = −2.910, β2 = 1083.714, β3 = −4.521) based on the impact of temperature fluctuations, bond wire diameter, and electrical stresses observed during power cycling tests. These adjustments provide a significant shift from traditional values, with the recalibrated models offering a better fit, as evidenced by a reasonable coefficient of determination (R2) and root mean square error (RMSE). Utilizing Monte Carlo simulations with a 5% uncertainty, the study calculates the B10 lifetimes of PV inverters, demonstrating a substantial reduction from 43 years in the unmodified model to 13 years in the modified model. This emphasizes the critical need for ongoing modification and validation of predictive models based on the actual operational data to enhance the reliability and efficiency of IGBTs in power electronic systems.

show abstract

Thermo-mechanical fatigue induced unexpected strain hardening of Cu clip wiring on transfer-mold type EV power modules

Kim

Noh

Park

et al. 2023

International Journal of Fatigue

View full text Add to dashboard Cite

Power cycling test of transfer molded IGBT modules by advanced power cycler under different junction temperature swings

Abstract: Power cycling test of transfer molded IGBT modules by advanced power cycler under different junction temperature swings

Cited by 9 publications

References 10 publications

Monte Carlo-Based Reliability Estimation Methods for Power Devices in Power Electronics Systems

Monte Carlo-Based Reliability Estimation Methods for Power Devices in Power Electronics Systems

Optimizing Insulated-Gate Bipolar Transistors’ Lifetime Estimation: A Critical Evaluation of Lifetime Model Adjustments Based on Power Cycling Tests

Thermo-mechanical fatigue induced unexpected strain hardening of Cu clip wiring on transfer-mold type EV power modules

Contact Info

Product

Resources

About