Conference Paper

NREL/CP-540-46417

June 2010 

Sensitivity of Solder Joint 

Fatigue to Sources of Variation 

in Advanced Vehicular Power 

Electronics Cooling

A. Vlahinos

Advanced Engineering Solutions

M. O’Keefe

National Renewable Energy Laboratory

Presented at the 2009 ASME International Mechanical 

Engineering Conference and Exposition

Lake Buena Vista, Florida

November 13−19, 2009
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1

Sensitivity of Solder Joint Fatigue to Sources of Variation in 

Advanced Vehicular Power Electronics Cooling*

Andreas Vlahinos

Advanced Engineering Solutions

Castle Rock, Colorado, USA

Michael O’Keefe

National Renewable Energy Laboratory

Golden, Colorado, USA

ABSTRACT

This paper demonstrates a methodology for taking 

variation into account in thermal and fatigue analyses of the die 

attach for an inverter of an electric traction drive vehicle. This 

method can be used to understand how variation and mission 

profile affect parameters of interest in a design. Three 

parameters are varied to represent manufacturing, material, and 

loading variation: solder joint voiding, aluminum nitride 

substrate thermal conductivity, and heat generation at the 

integrated gate bipolar transistor, or IGBT. The influence of 

these parameters on temperature and solder fatigue life is 

presented. The heat generation loading variation shows the 

largest influence on the results for the assumptions used in this 

problem setup.

INTRODUCTION

Power inverters are key components of the electric traction 

drives of hybrid electric, plug-in hybrid electric, fuel cell 

electric, and pure electric vehicles [1, 2]. Research and 

development of power inverters is currently focused on 

reducing the cost, weight, and volume of the technology while 

maintaining and/or increasing reliability [1, 2]. If the research 

goals related to cost, weight, volume, and reliability can be met, 

more advanced vehicles can enter the marketplace and reduce 

the amount of petroleum required for transportation.

Current-generation inverter designs used in today’s hybrid 

vehicles are built on proven technology that has demonstrated 

high reliability. In contrast, the next generation of inverter 

concepts combines new materials, new heat transfer methods, 

and new packaging concepts under increased loads and in 

smaller spaces. Furthermore, there is interest in expanding the 

range of temperatures and stresses under which these 

technologies can operate [3, 4]. For these new technologies and 

conditions, reliability is, as yet, unproven.

In a production environment, reliability data can be 

obtained from statistical measures of empirical data or from 

product testing. However, design changes during production to 

fix reliability problems are quite expensive. In contrast, during 

the early phases of research, design changes are cheap to make. 

However, prototypes may not even be available. Therefore, at 

the very earliest stages of design, other methods must be used 

to estimate reliability (see page 3 of [5] for further discussion). 

One such method is physical simulation, which we employ 

here.

Die attach failure has been reported as a critical failure 

mechanism in power electronics packages and will be the focus 

of this paper [5, 6]. Die solder joint fatigue is one form of die 

debonding failure. De-adhesion of the die is another major die 

debonding failure mechanism [5]. De-adhesion is mainly due to 

manufacturing defects such as excessive solder voiding or poor 

wetting of the solder [5]. In this study, we assume that the 

manufacturing quality is sufficient to avoid failure via deadhesion. Die attach fatigue results in cracking, which 

eventually causes the thermal resistance of the joint to increase. 

Thus, failure of the die attach solder typically results in failure 

of the power semiconductor due to exceeding the device’s

thermal limits [6].

In this paper, we explore the sensitivity of die attach solder 

joint fatigue to sources of variation for a baseline liquid-cooled 

power inverter (with pin-fin heat exchanger) placed in a hightemperature automotive environment. Sources of variation can 

come from the manufacturing process (variation in package 

geometry and/or some initial voiding during solder joint 

creation), the material properties, and the loading (coolant 

temperatures, flow rates, and heat inputs) [2]. Variations and 

uncertainty associated with these physical parameters exhibit 

probabilistic distributions (probability density functions). 

Therefore, the fatigue life (an output) will also exhibit a 

probability density function.

The modeling technique demonstrated here provides a 

framework for evaluating the effect of variation on solder joint 

fatigue prediction. Solder joint fatigue failure was chosen to 

study because it is an important failure mode for modern day 

automotive power inverters [5, 6].

*This paper was originally presented at the 2009 ASME 

International Mechanical Engineering Conference & 

Exposition, November 13-19, 2009, Lake Buena Vista, 

Florida (paper no. IMECE2009-11443).
2

There are numerous studies on solder joint reliability in the 

context of electronics packaging (see, for example, [7-11]). 

Analytical models have been proposed to estimate the 

thermally induced (elastic) stresses due to differences in 

coefficients of thermal expansion between adjacent layers in 

multilayered bonded materials (see, for example, [12-13]). In 

these studies, both experimental and analytical evidence 

indicates that stresses in “soft” lead-based soldered joints 

(similar to what is used in our analysis) are highest at the edges.

Reference [6] applies the finite element method to explore 

the failure of solder joints in power electronics packages. The 

authors use Anand’s viscoplastic model, which incorporates 

both plasticity and creep phenomena to describe the behavior of 

the solder joint. The authors are able to show that thermal 

cycling has a significant effect on solder joint reliability and 

recommend connecting the finite element model with a damage 

mechanics constitutive model to predict the number of cycles to 

failure.

In reference [2], the authors apply a suite of computeraided engineering tools, including finite element analysis, to 

study two reliability issues in power electronics modules: wire 

bond liftoff and substrate fracturing. The combined effects of 

process and material uncertainty on reliability are highlighted 

as concerns. The authors state that if a physics-of-failure model 

were available, an assessment of cycles to failure could be 

made.

MODEL DESCRIPTION

The physical model that we created for this study is 

presented in this section. We used a commercially available 

finite element code for simulation. We varied three parameters 

in this study: the heat generated from the IGBT (a variation in 

loading), the thermal conductivity of the IGBT solder joint 

(assumed to be due to the initial presence of voids), and the 

thermal conductivity of the substrate (a variation in material 

properties). These three properties were chosen to demonstrate 

the process of applying robust design techniques to the domain 

of power module thermal stress and reliability simulation. In 

truth, any parameter that can be modeled could have been 

chosen.

Model Overview

For this analysis, we considered a standard inverter design 

with a basic geometry similar to that of commercially available 

designs. The emphasis of this study is on demonstrating the 

analytical approach, although we will also point out some 

general insights that can be gained from the analytical results.

As an example to give the context of our model, Figure 1

shows the power inverter from a popular hybrid electric 

vehicle. The left-hand side of the inverter (circled by a dashed 

line) is used to power the main traction motor of the vehicle

and will be the focus of our subsequent discussion. The traction

motor inverter consists of 12 IGBTs and 12 diodes, and each 

pair of two IGBTs and two diodes (i.e., four devices) forms an 

electrical switch (each pair is electrically in parallel to reduce 

the amount of current any one device is exposed to). Electrical 

current is routed across the inverter through the metallization 

on the surface of the inverter and through wire bonds. Wire 

bonds are also used to deliver current from the gate driver (not 

shown) to the individual IGBTs to turn them on and off. A more 

extensive discussion of this inverter topology can be found in 

[14].

Our physical model is shown in Figures 2 and 3. The 

model represents a subset of the full vehicle inverter. We 

assume that the boundary conditions on the model correspond 

to the last device cooled along the cooling channel; this device 

typically experiences the hottest temperatures. Our model 

consists of one IGBT and diode pair and the layers of the 

inverter package between the devices and the cooling system.

The model is simplified to show only the relevant geometry. 

For example, wire bonds are not explicitly modeled.

It will be important in our model to get a correct prediction 

of heat transfer and temperatures because the stresses that cause 

fatigue in the solder joint are thermally induced due to 

differences in the coefficient of thermal expansion. For this 

reason, we will briefly discuss the thermal boundary conditions 

and relevant material properties before focusing on the 

interaction of model variation and fatigue results.

Figure 1. Example of Hybrid Electric Vehicle Inverter

Model Geometry

The geometry used for the devices is similar in size, shape, 

and layout to that of commercial hybrid inverters. In our 

design, we employ an elliptical pin-fin heat exchanger (see

Figure 2). The large rectangular region on the top of the model 

is the IGBT. The smaller square device is a diode. Below the 

IGBT and diode is a direct bond copper (DBC) substrate 

consisting of a top copper metallization layer, a substrate layer 

of aluminum nitride (AlN), and a lower copper layer. The IGBT 

and diode are soldered to the DBC. In turn, the DBC is soldered 

to the next layer down, which is a base plate. The base plate is 

fixed to the heat sink via bolts (not shown) and contains a 

thermal interface material (TIM) to create good thermal 

contact. Note that newer designs integrate the base plate and 

heat sink into one solid item. The advantage of having a 
3

separate heat sink and base plate is that inverter manufacturers

can create inverters separate from end-use heat exchanger 

designs. The disadvantage lies in the need for thermal interface 

materials that can cause a bottleneck for heat transfer.

Figure 2. Physical Model of Subsection of Inverter

The geometry of the inverter and thicknesses of the layers 

are shown in Figure 3 and Figure 4. Additional details,

including general trends for the heat transfer performance of

this inverter design, can be found in [15]. Note that the 

dimensions used are based on actual measurements from a

commercial inverter.

Figure 3. Layer Thicknesses and Materials

Figure 4. Inverter Subset Dimensions (mm)

Material Properties and Fatigue Model

The material properties used for the model were obtained 

from [16]. An important set of properties used in this study are 

solder fatigue properties which are given in Table 1 and 

estimated from the material properties and [17].

Table 1. Fatigue Properties of 63sn-37pb Solder

Fatigue Property Value

Fatigue Strength Coefficient (MPa) 93.3

Fatigue Strength Exponent -0.085

Fatigue Ductility Coefficient (MPa) 1.0 x 10

Fatigue Ductility Exponent

-6

-0.6

Cyclic Strength Coefficient (MPa) 93.3

Cyclic Strain Hardening Exponent 0.15

The solder joints can experience both elastic and plastic 

deformation during high-temperature excursions. The stresses 

that occur in the solder joint arise due to thermally induced 

stresses caused by differences in coefficients of thermal 

expansions between layers of the inverter module. The model 

we use to account for the elastic and plastic strain conditions is 

the Coffin-Manson strain-life relationship:

(1)

In (1), is the change in strain due to the application of 

our loading condition. The factor of 2 occurs because (1) is 

derived under the assumption of completely reversed loading—

i.e., a load is fully applied in one direction and then applied at 

the same magnitude in the opposite direction. Thus, the total 

change in strain for the application of a load in one direction is 

half the total. is the number of cycles to failure (the 

parameter of interest). is the modulus of elasticity. 

The remaining four terms are fatigue strength coefficient, 

, fatigue strength exponent, , fatigue ductility coefficient, 

, and fatigue ductility exponent, . The first term on the righthand side of (1) accounts for cycles to failure under elastic 

deformation, while the second term accounts for cycles to 

failure under plastic deformations. An in-depth derivation and 

discussion of this relationship and the parameters that are used 

can be found in Chapter 7-2 of [18] and Chapter 2 of [17]. A 

discussion of the engineering behind the fatigue module that 

implements the strain-life model in our finite element tool can 

be found in [19]. We are not currently set up to incorporate a 

viscoplastic effect with this model but are exploring its use in 

future models.

Thermal Boundary Conditions

The model is assumed to have adiabatic boundary 

conditions everywhere other than the heat sink. Thermal 

boundary conditions at the heat sink correspond to an average 

heat transfer coefficient of approximately 10,500 W/m2

.K at the 

pin-fins and 1,200 W/m2

The coolant being assumed is a 50/50 by mass mixture of 

water and ethylene glycol at 10 liters per minute flow rate total 

(equal to 5 liters per minute through the pin-fin array explicitly 

shown in the model). The coolant temperature under the device 

is assumed to be 105

.K on the underside of the heat sink. 

The heat transfer coefficients are estimated from a combination 

of computational fluid dynamics models and empirical 

correlations such as from [20].

o

C, which is a condition of interest to the 

FreedomCAR and Fuel Electrical and Electronics Technical 

IGBT or Diode, 

0.09mm

Solder, 0.127mm

Copper, 0.31mm

Substrate, 0.625mm

Copper, 0.31mm

Solder, 0.127mm

Base Plate, 2mm

Thermal Interface Material, 0.05mm

Pin Fin Cold Plate
4

Team. A discussion of the rationale and motivation for the 

FreedomCAR and Fuel Partnership, as well as the coolant 

temperature setting, can be found in [1].

Loading Cycle

Heat generation in the IGBT and diodes of an inverter 

during normal operation is due to a combination of on-state and 

switching losses. This heat is simulated in the model as a 

constant heat input at the IGBT and diodes, respectively. Heat 

is assumed to be transferred only through the heat sink. All 

other boundary conditions are assumed to be adiabatic. The 

inverter is typically packaged under the hood in a casing as part 

of a larger power module. A silicone gel is typically layered on 

the top of the inverter surface to protect it from direct exposure 

to the environment. Although heat may be conducted through 

the wire bonds themselves, we have taken the conservative 

assumption that no heat is transferred through the top of the 

inverter.

Although an automotive inverter is subjected to other 

loading conditions—most notably, vibrations and corrosive 

environments—we have chosen only one loading condition for 

consideration during this study.

The loading cycle used in this study is similar to power 

cycling. The simulation test is equivalent to heating the inverter 

under its own power to steady-state conditions and then 

allowing the inverter to cool back to the initial ambient 

condition. Note that we do not take transient phenomena such 

as creep into account during this process.

Variational Parameters

Three parameters of the inverter design were chosen to be 

stochastic in nature to study how these input parameters affect 

solder joint fatigue life. The first input parameter is heat 

generation at the IGBT, which represents a variation in loading. 

Note that the diode heat generation is a constant 15.5 W.

The next parameter is the thermal conductivity of the 

solder joint, where we are assuming that some initial voiding of 

the solder is affecting the overall thermal conductivity of the 

joint. This represents a variation in manufacturing. The impact 

of voids on thermal impedance depends on the type and 

location of the void and is nonlinear due to spreading resistance

[21, 22]. Thus, we do not have a direct correlation between 

solder void fraction and thermal impedance. We assume that 

there is no significant voiding near the corners, where we 

expect the solder to initially fatigue.

The third parameter we explore is the thermal conductivity 

of the AlN substrate, which represents variation in material 

properties.

The probability density functions for these three 

parameters have been estimated from the following sources. 

For the heat generation, estimates were taken from a study of 

heat generation in a Toyota Prius test car, but scaled up to levels 

corresponding to the FreedomCAR and Fuel partnership targets 

for a 55 kW traction motor system (see [23] for details). The 

variation in thermal conductivity of the solder joint is assumed 

to arise from variations in solder material properties and 

variation in void fraction of the solder. Reference [21] gives a 

good correlation between void percentage and increase in 

thermal impedance. Finally, the variation in the AlN thermal 

conductivity is an estimate based on the range of material 

properties seen for available products [24-27].

A graphical representation of the sampled probability 

density functions for these variational parameters is given in

Figure 5. The ordinate or vertical axis for each parameter shows 

the number of simulation runs carried out at the given value 

along the abscissa or horizontal axis. The actual distributions of 

the variational parameters are not known, so normal 

distributions were assumed.

Figure 5. Variational Parameter Probability Density 

Functions

WORKFLOW

Simulation proceeds by inputting values from the 

categories of geometry and boundary conditions, material 

properties, and loading profiles into the physical models. A 

suite of analytical tools then runs a thermal simulation and a 

structural simulation; the Coffin-Manson relation is then used 

to estimate fatigue of the solder joint. Finally, the outputs from 

the various physical models are obtained. This process is 

depicted graphically in Figure 6. Variational parameters are 

handled by sampling various combinations of the input values 

and rerunning the simulation tool suite. Note that multiple runs 

40 50 60 70 80 90 100

0

1000

2000

3000

4000

 Thermal Conductivity of IGBT Solder Joint (W/m-K)

 Probability Density

0 50 100 150 200 250

0

1000

2000

3000

4000

 Thermal Conductivity of ALN (W/m-K)

 Probability Density

30 40 50 60 70 80 90 100 110

0

1000

2000

3000

4000

 IGBT Heat Generation (W)

 Probability Density
5

can be performed very quickly under conditions in which the 

input loading changes by some constant factor in comparison to 

a reference case. Under these circumstances, only the reference 

case needs to be fully run, and the results can be scaled to 

determine all other cases.

Figure 6. Simulation Workflow

The sampling of two variational parameters (AlN thermal 

conductivity and solder joint thermal conductivity) is depicted 

in Figure 8.

RESULTS

The thermal and fatigue results are presented in the 

sections that follow. In addition, we show how concepts from 

robust design could be applied to interpret the results.

Thermal Results

Because the magnitude of the heat generated by the IGBT 

is higher than that of the diode, we see the highest temperatures 

consistently occurring on the IGBT device itself. Maximum 

temperature varies stochastically with the input variable 

distributions, and the IGBT heat rejection is the most 

significant. A snapshot of the temperature distribution across 

the model is given in Figure 7. The output distribution of 

maximum IGBT temperature is given in Figure 10. A maximum 

specification limit of 150o

C is assumed for the IGBT.

Figure 7. Temperature Distribution

(Tmax = 138.8)

Figure 8. Sampling Variational Parameters

40 50 60 70 80 90 100 0

100

200

300

400

500

600

 Thermal Conductivity of IGBT Solder Joint (W/m-K)

40 50 60 70 80 90 100 40

50

60

70

80

90

100

 Thermal Conductivity of ALN (W/m-K)

 Thermal Conductivity of IGBT Solder Joint (W/m-K)

0 100 200 300 400 500 600 30

40

50

60

70

80

90

100

 Thermal Conductivity of ALN (W/m-K)

40

60

80

100

40

60

80

1000

50

100

150

 K of IGBT Solder Joint K of ALN

 Q
6

Fatigue Results

In this section, we look at the cycles to failure of the IGBT

solder joint. For a discussion of failure prediction for other 

solder joints in the package, see [28]. We define failure to

represent the number of cycles until the onset of cracking in the 

solder joint. Upon onset of cracking, the device may survive 

additional cycles as the crack propagates and eventually causes 

the effective thermal conductivity to get so low that the device 

junction temperature goes above specification limits and/or the 

die becomes completely unattached.

The highest areas of stress occur at the edges and corners,

resulting in cracks propagating from these locations. This can 

be seen in the plot of cycles to failure in Figure 9. This same 

phenomenon can be seen in the literature [29, 10] and can be 

explained through simple analytical models of stresses in 

epitaxial layered devices (see, for example, [12]).

Figure 9. Fatigue Life of IGBT Solder

Robust Design Investigation

In this section, we show the output distributions that arise 

from the stochastic inputs used (see Figure 5). In Figure 10, the 

distribution of maximum IGBT temperature is shown. As can 

be seen, the output distribution of maximum junction 

temperature is within an acceptable range for the problem setup 

chosen. The results are normally distributed, and the number of 

standard deviations away from the mean is plotted on the 

graphs.

A cycle life of 22,000 cycles was selected for a desired life 

of this product based on 4 cycles per day, 365 days per year, 

and a target 15-year life. Figure 11 shows the distribution of 

cycles to failure and indicates that the IGBT die attach, under 

the given conditions, would survive the 15-year life with >99% 

confidence.

The influence of the input parameters on the final results is 

presented in Figure 12 and Figure 13. The influence is 

calculated by normalizing the difference between the output 

result when the input parameter is high and when the input 

parameter is low. As can be seen, the thermal loading has the 

highest influence on both the solder joint reliability and the 

maximum package temperature, which indicates the importance 

of knowing the usage environment for reliability work.

CONCLUSIONS

This paper presented a methodology for taking variable 

input parameters into account during a solder die attach fatigue 

analysis for an automotive inverter of an electric traction drive

vehicle. Since the inverter, its boundary conditions, and loading 

conditions were invented for the purpose of this analysis, we 

must be careful in drawing specific conclusions about overall 

inverter performance. Specifically, several failure mechanisms 

associated with an automotive inverter are not taken into 

account in the current study (for example, wire bond fatigue 

failure and substrate cracking). Furthermore, our failure physics 

model did not take viscoplastic effects such as creep into 

account.

For the conditions evaluated in this study, the thermal 

loading condition was shown to have the strongest effect on the 

output parameters of temperature and fatigue life. Although we 

did not look at an extensive list of variational parameters, the 

large impact that heat generation has on fatigue life highlights 

the importance of understanding the mission profile to which 

the inverter will be subjected.

Using the design process presented, we have shown that 

one may be able to estimate the fatigue life of a power inverter

for automotive applications using commercially available 

software. This method allows the designer to understand how 

variation in input parameters and mission profile can affect 

metrics of interest, such as fatigue life.

Further work on transient heat generation should be 

conducted using vehicle systems tools to better estimate a 

loading profile in place of the simple loading cycle used in this 

study. Additional loads, such as vibrations, should also be taken 

into account along with a more comprehensive analysis of 

additional failure modes and mechanisms (such as wire bond 

flexural fatigue and substrate cracking). Validation testing will 

be critical to confirm model predictions. Once these additions 

are made to the scope of the problem, a meaningful robust 

design optimization can be attempted.
7

Figure 10. Maximum IGBT Temperature Distribution

Figure 11. Distribution of Cycles to Failure of IGBT Solder Joint

2 2.5 3 3.5 4 4.5 5

x 104

0

100

200

300

400

500

600

700 μ = 35708 Cycles,σ = 1705

-σ σ

-2σ 2σ

-3σ 3σ

 4σ -4σ

 5σ

 6σ

 Target Cycles

 Cycles to Failure for IGBT Solder Joint

 Relative Frequency
8

Figure 12. Influence of Inputs on Maximum 

Temperature

Figure 13. Influence of Inputs on IGBT Solder Fatigue

NOMENCLATURE

IGBT integrated gate bipolar transistor

change in strain due to loading

number of cycles to failure

modulus of elasticity (Young’s Modulus)

fatigue strength coefficient

fatigue strength exponent

fatigue ductility coefficient

fatigue ductility exponent

PDF probability density function

ACKNOWLEDGMENTS

We would like to acknowledge Susan Rogers of the U.S.

Department of Energy’s Vehicle Technologies Program for 

funding this effort.

REFERENCES

[1] FreedomCAR & Fuels Electrical and Electronics 

Technical Team. (November 2006). “Electrical and Electronics 

Technical Team Roadmap,” online at 

http://www1.eere.energy.gov/vehiclesandfuels/pdfs/program/ee

tt_roadmap.pdf

[2] C. Bailey, C., Tilford, T., and Lu, H., 2007, “Reliability 

Analysis for Power Electronics Modules,” presented at the 30th 

IEEE International Spring Seminar on Electronics Technology, 

Cluj-Napoca, Romania, May 9-13, 2007.

[3] McCluskey, F. P., 2007, Power Modulation 

Investigation for High Temperature (175o

C–200 o

[4] Zhu, N., Van Wyk, J. D., and Liang, Z. X., 2004, 

“Thermal-Mechanical Stress Analysis in Embedded Power 

Modules,” IEEE Technical Paper, Presented at the 35

C) Automotive

Applications, Oak Ridge National Laboratory Technical Report 

no. ORNL/TM-2007/046.

th

[5] McCluskey, F. P., 2006, “Power Module Reliability in 

High Temperature Applications: Interim Report on the Results 

of Phase I,” Dept. of Mechanical Engineering, University of 

Maryland, College Park, MD, Subcontractor Report submitted 

to Oak Ridge National Laboratory.

Annual 

IEEE Power Electronics Specialists Conference in Aachen, 

Germany, pp. 4503-4508.

[6] Ye, H., Lin, M., and Basaran C., 2002, “Failure Modes 

and FEM Analysis of Power Electronic Packaging,” Finite 

Elements in Analysis and Design, vol. 38, 2002, pp. 601-612.

[7] Frear, D. , Grivas, D., and Morris, J.W., Jr., “Parameters 

Affecting Thermal Fatigue Behavior of 60Sn-40Pb Solder 

Joints,” Journal of Electronic Materials, vol. 18, no. 6, 1989, 

pp. 671-680.

[8] Shaw, M.C., 2003, “High-Performance Packaging of 

Power Electronics,” MRS Bulletin, vol. 28, no. 1, pp. 41-50.

[9] He, J., Shaw, M.C., Mather, J.C., and Addison, R.C., 

Jr., 1998, “Direct Measurement and Analysis of the TimeDependent Evolution of Stress in Silicon Devices and Solder 

Interconnections in Power Assemblies,” 33rd IAS Annual 

Meeting, IEEE Industry Applications Conference, St. Louis, 

MO.

[10] Shaw, M. C., He, J., Mather, J. C., and Addison, R. C. 

Jr., 2000, “Effects of Plasticity on Reliability in Multilayered 

Electronic Packages,” IEEE technical paper presented at the 

2000 Inter-Society Conference on Thermal Phenomena, pp. 

279-286.

[11] Stinson-Bagby, K., Huff, D., Katsis, D., Van Wyk, D., 

and Lu, G.Q., 2004, “Thermal Performance and 

Microstructures of Lead versus Lead-Free Solder Die Attach 

Interface in Power Device Packages,” presented at the 2003 

International Symposium on Microelectronics, pp. 27-32.

[12] Suhir, E., 1986, “Stresses in Bi-Metal Thermostats,” 

Journal of Applied Mechanics, vol. 53, pp. 657-660.

[13] Ru, C., 2002, “Interfacial Thermal Stresses in 

Bimaterial Elastic Beams: Modified Beam Models Revisited,” 

Journal of Electronic Packaging, vol. 124, pp. 141-146.

[14] Staunton, R. H., Ayers, C. W., Marlino, L. D., 

Chiasson, J. N., and Burress, T. A., May 2006, Evaluation of 

2004 Toyota Prius Hybrid Electric Drive System, Oak Ridge 

National Laboratory Technical Report, ORNL/TM-2006/423.

[15] O’Keefe, M., and Bennion, K., 2007, “A Comparison 

of Hybrid Electric Vehicle Power Electronics Cooling Options,”
9

presented at the 3rd

[16] Lau, J. H., and Pao, Y. H., 1997, Solder Joint 

Reliability of BGA, CSP, Flip Chip, and Fine Pitch SMT 

Assemblies, McGraw Hill, New York.

Annual IEEE Vehicle Power and Propulsion 

Systems Conference. Arlington, TX, September 9-12, 2007, pp. 

116-123.

[17] Bannantine, J. A., Comer, J. J., and Handrock, J. L.,

1990, Fundamentals of Metal Fatigue Analysis, Prentice-Hall, 

New York.

[18] Shigley, J. E., and Mischke, C. R., 1989, Mechanical 

Engineering Design, 5th

[19] Hancq, D., Walters, A., and Beuth, J., 2000,

“Development of an Object-Oriented Fatigue Tool,” 

Engineering with Computers, vol. 16, pp. 131-144.

Edition, McGraw-Hill, Inc., New York, 

pp. 272-273.

[20] Montelpare, S., and Ricci, R., 2004, “An 

Experimental Method for Evaluating the Heat Transfer 

Coefficient of Liquid-Cooled Short Pin-Fins Using Infrared 

Thermography,” Experimental Thermal and Fluid Science, vol. 

28, pp. 815-824.

[21] Zhu, N., 1999, “Thermal Impact of Solder Voids in the 

Electronic Packaging of Power Devices,” Proceedings of the 

15th

[22] Biswal, L., Krishna, A., and Sprunger, D., 2005,

“Effects of Solder Voids on Thermal Performance of a High 

Power Electronic Module,” Proceedings of the 7

IEEE SemiTherm Symposium, pp. 22-29.

th

[23] O’Keefe, M., Bennion, K., and Albright, G., 2007, 

HEV Inverter Thermal Duty Cycles, National Renewable 

Energy Laboratory Report No. MP-540-41801, Golden, CO.

Electronics 

Packaging Technology Conference, vol. 2, pp. 526-531.

[24] Material Properties for Aluminum Nitride from 

Accuratus, online at http://www.accuratus.com/alumni.html.

[25] NTK Spark Plug Co., Ltd., 2002, “Aluminum Nitride 

(AlN) Ceramic Package/Substrate,” online presentation,

http://www.ntktech.com/AlN/ALN%20for%20web.pdf.

[26] Franco Júnior, A., and Shanafield, D. J., 2004,

“Thermal Conductivity of Polycrystalline Aluminum Nitride 

(AlN) Ceramics,” Cerâmica, vol. 50, no. 315, pp. 247-253, São 

Paulo, Brazil, July 2004.

[27] Savrun, E., and Nguyen, V., 2006, “High Thermal 

Conductivity Aluminum Nitride for High Power Microwave 

Windows—An Update,” Sienna Technologies white paper,

online at 

http://www.siennatech.com/HIGH%20THERMAL%20CO%C9

AVE%20WINDOWS.pdf

[28] O’Keefe, M., and Vlahinos, A., 2009, “Impacts of 

Cooling Technology on Solder Fatigue for Power Modules in 

Electric Traction Drive Vehicles,” presented at the 2009 Vehicle 

Power and Propulsion Systems Conference, Dearborn, MI, 

September 7-11, 2009.

[29] He, J., Shaw, M. C., Mather, J. C., and Addison, R. C. 

Jr., 1998, “Direct Measurement and Analysis of the TimeDependent Evolution of Stress in Silicon Devices and Solder 

Interconnections in Power Assemblies,” Proceedings of the 33rd

IAS Annual Meeting, 1998 IEEE Industry Applications 

Conference, St. Louis, MO, vol. 2, pp. 1038-1045.
F1147-E(10/2008)

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4. TITLE AND SUBTITLE

Sensitivity of Solder Joint Fatigue to Sources of Variation in 

Advanced Vehicular Power Electronics Cooling

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DE-AC36-08-GO28308

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A. Vlahinos, Advanced Engineering Solutions

Michael O'Keefe, NREL

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14. ABSTRACT (Maximum 200 Words)

This paper demonstrates a methodology for taking variation into account in thermal and fatigue analyses of the die 

attach for an inverter of an electric traction drive vehicle. This method can be used to understand how variation and 

mission profile affect parameters of interest in a design. Three parameters are varied to represent manufacturing, 

material, and loading variation: solder joint voiding, aluminum nitride substrate thermal conductivity, and heat 

generation at the integrated gate bipolar transistor. The influence of these parameters on temperature and solder 

fatigue life is presented. The heat generation loading variation shows the largest influence on the results for the 

assumptions used in this problem setup.

15. SUBJECT TERMS

power electronics; power electronics cooling; solder joint fatigue analysis 

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