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Research Papers

Efficient Thermal-Impedance Simulation of Insulated-Gate Bipolar Transistors Modules on Heat Sinks

[+] Author and Article Information
Thomas B. Gradinger

e-mail: thomas.gradinger@ch.abb.com

Uwe Drofenik

e-mail: uwe.drofenik@ch.abb.com
ABB Switzerland Ltd.,
Corporate Research,
Segelhofstrasse 1K,
Baden-Dättwil 5405, Switzerland

1Corresponding author.

Manuscript received August 7, 2012; final manuscript received February 8, 2013; published online October 3, 2013. Assoc. Editor: Mehmet Arik.

J. Thermal Sci. Eng. Appl 5(4), 041009 (Oct 03, 2013) (11 pages) Paper No: TSEA-12-1128; doi: 10.1115/1.4023889 History: Received August 07, 2012; Revised February 08, 2013

The prediction of temperatures in power semiconductor modules, such as insulated-gate bipolar transistors (IGBTs) is critical to ensure adequate lifetime modeling of the devices. A temperature of particular interest is that of the semiconductor junction, which is used to assess the lift-off of wire bonds. For many applications featuring dynamic loads, the junction temperature needs to be simulated for so-called mission profiles of significant duration. To limit the computational expense, the simulations are based on thermal impedances from junction to ambient, which may be obtained from numerical 3-d simulations. Even these 3-d simulations can be computationally expensive. In power-electronic systems, often, large heat sinks are used with a multitude of mounted IGBT modules, interacting thermally. In such cases, the detailed 3-d models become large and the transient simulations are not feasible. In the present work, a method is proposed that allows us to significantly reduce the 3-d model size. To this end, the ideas of compact or boundary-condition-independent models are used. The presented method has the advantage that, unlike in model-order reduction, the system matrices of the 3-d model are not needed. This makes the method applicable to commercial simulation software like ANSYS Icepak™, that does not give access to the system matrices. The method is implemented via MATLAB™ scripts that automatically generate 3-d ANSYS Icepak™ models of IGBT modules on a heat sink. An example case of two IGBT modules mounted on an air-cooled heat sink is presented, and the method is shown to yield good accuracy (thermal-impedance errors below 8% and thermal-resistance errors close to zero), while reducing the model's mesh size by the factor of 14. Further error reduction is expected to be possible by adapting the model parameters. This can be subject to future work.

Copyright © 2013 by ASME
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References

Figures

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Fig. 1

Heat sink with 8 IGBT modules, e.g., S1–6 belonging to an inverter, and S7–8 belonging to a braking chopper. Slice of half-module width shaded gray.

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Fig. 2

Example case of 2 HiPak™ IGBT modules on a heat sink, corresponding to the slice shaded gray in Fig. 1

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Fig. 3

Detailed Icepak™ model of the case shown in Fig. 2. Computational mesh, cross-sectional view in the z-direction.

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Fig. 4

Detailed Icepak™ model of the case shown in Fig. 2. Computational mesh, cross-sectional view of half an IGBT module in the y-direction.

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Fig. 5

Simulation process

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Fig. 6

IGBT-module geometry, top view. Left half corresponding to each of the two module halves on the heat sink in Fig. 2. Block-model segmentation shown for the lower left quadrant. Squares within shaded areas show sources of detailed Icepak™ model. Faces 10, 14, and 27 numbered for later reference. Hatched face in lower-right corner is set to elevated temperature to check time step influence (Sec. 5.1).

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Fig. 8

Simplified Icepak™ model of the case shown in Fig. 2, using block models for the IGBT modules. Computational mesh, cross-sectional view in the z-direction.

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Fig. 9

Simplified Icepak™ model of the case shown in Fig. 2, using block models for the IGBT modules. Computational mesh, cross-sectional view of half an IGBT module in the y-direction.

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Fig. 10

Comparison of Zth(j-a) from detailed model on heat sink. “Direct” = determination from monitor points. “Via convolution” = determination via Eq. (2).

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Fig. 11

Normalized error of Zth(j-a) obtained via convolution in Fig. 10 (≡(Zvia conv.-Zdirect)/Zdirect)

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Fig. 7

Flow networks modeling cooling-air flow in Icepak™

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Fig. 13

Comparison of Gik(t) between block model and detailed Icepak™ model. Examples for faces 10, 14, and 27. For the detailed model, the curves Gik and Gki overlap.

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Fig. 12

Comparison of qmk(t) between block model and detailed Icepak™ model. Examples for faces k = 10 and 14, for IGBTs and diodes heated.

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Fig. 14

Zth(j-a) for IGBTs, diodes and cross-talk (“IGBT to diode” meaning “IGBTs heated, diodes measured”): comparison of detailed Icepak™ model and block model

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Fig. 15

Normalized error in Zth(j-a) of block model ((Zblock-Zdetail)/Zdetail) for IGBTs, diodes, and cross-talk (“IGBT to diode” meaning “IGBTs heated, diodes measured”): comparison of detailed Icepak™ model and block model

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