New Trends and Developments in Automotive System Engineering Part 5 pptx

New Trends and Developments in Automotive System Engineering

148

Fig. 1. (A) After 160 cycles, and (B) after 320 cycles. Note the macroscopic cracks
propagating on the friction surface along the radial direction, extending from the inner to
the outer radius of the disc [Maluf, 2007].
is clear that cracking in brake discs should be seen as an isothermal and thermomechanical
problem. Isothermal Fatigue (IF) consists in the application of a variable mechanical strain at
a constant temperature. The main advantages of this test are its simplicity and lower cost
than that of anisothermal tests (thermomechanical).
Until recently, the fatigue strength of materials at high temperatures was estimated based
on IF tests at the maximum temperature expected in the Thermal Fatigue (TF) cycle.
However, this procedure proved to be insufficient because the strength of materials
in TMF is significantly lower than that expected for the IF-based estimate. This is due
to mechanisms possibly activated during the thermal cycling of TMF, which does not occur
in IF, where the temperature is kept constant.
There are two main types of brake systems: drum and disc. The use of disc in place of drum
brakes in heavy vehicles has become increasingly common in recent years.
This is due mainly to the search for greater braking efficiency, since disc brakes withstand
higher temperatures than drum brakes [BOIOCCHI, 1999]. However, simply changing the
drum shoe for the disc pad system does not suffice, making it necessary to analyze the brake
system as a whole, as well as its influence on the vehicle’s performance and safety.
In many high responsibility applications – as in the case of brake discs, knowing the results
of tensile, impact and hardness testing is not enough to characterize the materials used in
components, because these results cannot provide the information needed to reliably predict
the behavior of these parts in real working conditions. Ideally, the materials used in brake
systems should possess several properties such as good thermal conductivity, good
corrosion resistance, good durability, stable friction, low wear rate and good cost-benefit
[WEINTRAUB, 1998].

1.1 Thermomechanical Fatigue – TMF
Several components are subject to a variety of thermomechanical and isothermal loading
due to temperature variations during a vehicle’s operation. The cyclic loading conditions
induced by temperature gradients are essentially loads limited by strain. Therefore,
laboratory studies of Isothermal Fatigue, IF, are usually limited by strain control in low cycle
fatigue tests [HETNARSKI, 1991].
Thermomechanical and Isothermal Fatigue Behavior of Gray Cast Iron for Automotive Brake Discs

149
Thermomechanical fatigue, TMF, describes fatigue under simultaneous variation of
temperature and mechanical strain. Mechanical strain, which is determined by subtracting
the thermal strain from the total strain, should be uniform in every specimen and originates
from external restrictions or loads applied externally, e.g., if a specimen is held between two
rigid walls and subjected to thermal cycling (without allowing expansion), it will undergo
external compressive mechanical strain. Examples of TMF can be found in pressure vessels
and pipes in the electric power industry, where structures undergo pressure loads and
thermal transients with temperature gradients in the thickness direction, and in the
aeronautical industry, where turbine blades and discs undergo temperature gradients
superimposed to rotation-related stresses.

According to Sehitoglu [SEHITOGLU, 1996] TMF may involve several mechanisms in
addition to fatigue damage, including creep at high temperatures and oxidation, which
contribute directly to damage. These mechanisms differ depending on the history of strain
and temperature. They are different from those foreseen by the phenomenon of creep tests
(non-reverse) and by oxidation tests in the absence of stresses (or of constant stresses).
Microstructural degradation may occur under TMF in the form of:
1. Overaging, such as the coalescence of precipitates and formation of lamellae;
2. Strain aging, in the case of solid solution hardening systems;
3. Precipitation of secondary phase particles; and
4. Phase transformation within the cycle’s ultimate temperature.

Variations in the mechanical properties or in the coefficient of thermal expansion in the
matrix and precipitates, which are present in many alloys, also result in local stresses and
cracks. These mechanisms influence the material’s strain characteristics, which are
associated with damage processes.
1.2 Isothermal Fatigue – IF
IF test consists of imposing variable mechanical strains while maintaining the temperature
constant. This type of test has been widely employed since the 1970s, with the advent of test
machines operating in closed cycle. The main advantages of this test are its simplicity and
low cost when compared to anisothermal tests, and results for a variety of materials are
available in the literature [COFFIN Jr, 1954].
Observations by researchers have shown that service life under IF is longer than that found
in anisothermal fatigue [HETNARSKI, 1951; SHI et al., 1998]. This was reported by Shi et al.
[SHI et al., 1998] in a study of a molybdenum alloy containing 0.5% of Ti, 0.08% of Zr and C
in the range of 0.01 to 0.04%, see Figure 2.
The lifes obtained in IF tests at two temperature levels studied, 350
o
C and 500
o
C, were
higher, in both cases, than those found in TMF in phase for temperatures from 350
o
C to
500
o
C, demonstrating that temperature variations cause extensive damage of the material.
However, no obvious difference was found between the two isothermal tests analyzed
regarding the number of cycles to failure of the specimens, confirming that in this
temperature range the material maintains a good cyclic resistance. Hence, designs based
solely on the isothermal fatigue of components that work at high temperatures are not
reliable, thus requiring a more in-depth study of the behavior of the materials subjected to

this phenomenon, including tests at different temperature intervals (anisothermal fatigue)
and in a variable range of stresses and strains.
Figure 3 indicates that the longest IF life of specimens occurs within an intermediary range
of the applied temperature. In this range, the shortest life found for 316L (N) austenitic

New Trends and Developments in Automotive System Engineering

150

Fig. 2. IF and TMF curves [SHI et al., 1998].


Fig. 3. Influence of temperature on the fatigue life [SRINIVASAN et al., 2003
stainless steel was found at ambient temperature at which the strain induced the formation
of martensite phase.
The microstructural recovery of the material, which was responsible for the increased life,
occurred at the temperature of 573 K (300
º
C). The reduction of life with continuous
increases in temperature is attributed to several effects of dynamic strain, such as the
concentration of stresses produced in sites of stacking unconformities when the maximum
stress of the cycle is reached, causing an increase in crack growth rate.
This is clearly evident at temperatures above 873 K (600
o
C), at which the lifetime was
significantly reduced by oxidation [SRINIVASAN et al., 2003].
Another aspect to be observed under in IF with controlled strain is the behavior of cyclic
stress as a function of life. The behavior of the 316L (N) austenitic stainless steel was
monitored during four stages, as illustrated in Figure 4 [SRINIVASAN et al., 2003].
Thermomechanical and Isothermal Fatigue Behavior of Gray Cast Iron for Automotive Brake Discs

151

Fig. 4. Cyclic stress response as a function of temperature [SRINIVASAN et al., 2003].
The alloy exhibited a brief period of cyclic hardening, reaching its maximum stress in the
early stage of life, followed by cyclic softening before attaining the stable regime. In the
period prior to fracture, the stress amplitude decreased rapidly, indicating crack nucleation
and propagation.
This figure also shows that the amplitude of the peak stress increased with rising
temperature from 573 to 873 K, and also that some factors contribute to the drop in the
material’s strength with the increase in temperature. These factors are an abnormal cyclic
hardening rate and reduction of the amplitude of plastic strain in the lifetime intermediary
to fracture, and an increase in the maximum stress rate in the initial cycles in response to
increased temperature, which develop due to the inductive interaction between diffusion
solutes and mobility of the unconformities during strain. All these phenomena are
considered manifestation processes of the period of dynamic strain.
2. Materials and methods
Table 1 lists the chemical composition of the four gray cast iron alloys that are used in the
production of automotive brake discs and that were the object of this study.
After selecting these four alloys, isothermal and thermomechanical fatigue tests were
performed on specimens in conditions of strain, in-phase and out-of-phase. The failure
criterion adopted was a 50% decrease of the maximum load reached during the test. .
Figure 5 (a) shows a Y-shaped block, according to the ASTM A476/476M standard,
indicating regions A and B from which the test specimens were removed. Figure 5 (b) shows
the dimensions and geometry of the test specimens used in the IF and TMF tests.
Samples were removed from regions A and B of the Y-shaped blocks to machine fabricate
the specimens for the TMF and IF tests, as indicated in Figure 5b.
TMF and IF tests were performed in the Laboratory of Mechanical Properties of the
Department of Materials, Aeronautics and Automotive Engineering at the Engineering
School of São Carlos, University of São Paulo. All tests were conducted in a 250 kN capacity

New Trends and Developments in Automotive System Engineering

152
Alloys
Elements
A B C D
%C
3.36 3.45 3.71 3.49
%Si
2.07 2.11 2.0 1.87
%Mn
0.63 0.71 0.69 0.53
%P
0.03 0.068 0.059 0.03
%S
0.06 0.05 0.052 0.11
%Cr
0.16 0.30 0.19 0.29
%Mo
0.06 0.41 0.42 -
%Cu
0.08 0.10 0.40 0.52
Table 1. Cast iron alloys chemical composition (weight %)




Fig. 5. (A) Y-shaped block according to the ASTM A476/476M standard, showing regions A
and B from which the specimens were removed, and (B) geometry and dimensions of

specimen used in the TMF and IF tests, dimensions in mm.
MTS 810 servo-hydraulic testing system, equipped with an MTS Micro Console 458.20
controller, Figure 6 and specially adapted to for TMF tests under total strain control. A high
temperature axial strain gauge, MTS model 632.54F-14, was used to control the amplitude of
total strain. The hydraulic grip system was an MTS model 680.01B, which is suitable for
mechanical tests at high temperatures.
The test specimens were heated in a 75 kW inductive heating system operating at a
frequency of 200 kHz. The temperature was measured using an optical pyrometer equipped
with a laser target focused midway along the length of the specimen, providing the input for
the temperature controller, which received the command signal from a microcomputer. The
temperature gradient along the specimen length was minimized using an induction coil
with optimized geometric dimensions. The auxiliary cooling system of the clamps grips for
the thermomechanical fatigue tests consisted of two spiral copper tubes for circulating cold
water and two compressed air pipes attached at to the upper and lower ends of the clamps
grips. Figure 7 shows a localized detailed view of the region where the test specimen was
fixed in the MTS 810 machine.
(A)
(B)
Thermomechanical and Isothermal Fatigue Behavior of Gray Cast Iron for Automotive Brake Discs

153



Fig. 6. Overall view of the testing apparatus, showing the induction furnace and the MTS
810 servo-hydraulic testing system.

Fig. 7. Detail of the specimen, induction coil, auxiliary cooling system of the grips, and the
strain gauge with ceramic rods used in the tests.
The TMF tests were performed in thermal cycles of 120s, the minimum time required to
allow for stable cooling of the gray cast iron specimen and to maintain synchronism
between the thermal and mechanical cycles, load ratio, R= -1, as illustrated in Figures 8 (a)
and (b).
In-phase and out-of-phase TMF tests were carried out in the temperatures from 300 to
600°C. For in-phase TMF, positive strain corresponds to the maximum temperature of the
cycle, negative strain corresponds to the minimum temperature of the cycle, and strain is
equals zero at the temperature of 450°C, as illustrated in Figure 9.
New Trends and Developments in Automotive System Engineering

154


0 20 40 60 80 100 120
-0,8
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8

Alloy A
Total Strain
Temperature
Time [s]

ε
Total
[%]
250
300
350
400
450
500
550
600
650
Temperature [°C]


(A)


0 20 40 60 80 100 120
-0,2
-0,1
0,0
0,1
0,2

Alloy A
Total Strain
Temperature
Time [s]
ε

Total
[%]
250
300
350
400
450
500
550
600
650
Temperature [°C]


(B)
Fig. 8. Variation of total strain as a function of time and temperature, in initial cycles of TMF
tests on alloy A, under controlled mechanical strain (0.4%): (A) in-phase, and (B) out-of-
phase.
Thermomechanical and Isothermal Fatigue Behavior of Gray Cast Iron for Automotive Brake Discs

155
-0,6 -0,4 -0,2 0,0 0,2 0,4 0,6
250
300
350
400
450
500
550
600

650
Alloy
A (ε
m
=0.4%)


Temperature [°C]
ε
Total
[%]

Fig. 9. Temperature hysteresis loop as a function of total strain in an in-phase TMF test.
Hysteresis loop for alloy A.
In out-of-phase TMF tests, the positive strain corresponds to the lower cycle temperature,
negative strain to the higher cycle temperature, and strain is zero at 450
°
C, as indicated in
Figure 10.
-0,15 -0,10 -0,05 0,00 0,05 0,10 0,15 0,20
250
300
350
400
450
500
550
600
650
Alloy

A (ε
m
=0.4%)


Temperature [°C]
ε
Total
[%]

Fig. 10. Temperature hysteresis loop as a function of total strain in an out-of-phase TMF test.
3. Results and discussion
The behavior of total strain amplitude (Δε
m
/2) as a function of the number of cycles to
failure was obtained in alloys A, B, C and D for several levels of strain in the thermal cycle
from 300 and 600ºC. It was found that the higher the total strain applied the shorter the
lifetime of the material, which is due to the increase in stress required to reach higher
strains.
New Trends and Developments in Automotive System Engineering

156
Figure 11 presents the curve of total strain amplitude, Δε
t
/2, vs. the number of reversals to
failure (2N
f
), indicating the behavior of the four alloys tested in-phase. As can be seen, at
mechanical strain amplitude of 0.10% in the in-phase test condition, the alloys exhibited an
anomalous behavior, i.e., they presented premature fatigue life values than those obtained

in the tests at higher amplitudes of mechanical strain. This was very likely due to the
occurrence of the phase transformation known as graphite expansion caused by
decomposition of the cementite phase in the perlite microconstituent, which transforms into
ferrite and vein graphite [ASM International handbook, 1999].
This microstructural transformation leads to a significant decrease in the alloy’s mechanical
strain amplitude values, producing a rapid drop in the applied tensile load as a function of
the number of reversals to failure. This demonstrates the non-validation of the fatigue life
criterion adopted in the condition of 50% decrease of the ultimate load, to study the
mechanical behavior of gray cast iron loaded under thermomechanical fatigue at very low
levels of mechanical strain amplitude.
Thus, since the results for the strain amplitude of 0.1% are not valid, they were disregarded
in the construction of the tendency lines in Figure 11.
10 100 1000 10000
0,1
0,2
0,3
0,4
0,5




2N
f
[cycles]
Δε
m
/ 2 [%]
Alloys
(In Phase)

A
B
C
D

Fig. 11. Comparative plot of the mechanical strain amplitude of the four alloys as a function
of the number of reversals to failure in the TMS in-phase condition.
The results obtained in the in-phase loading condition indicate that the behavior of the gray
cast iron alloys A, B, and C in in-phase TMF were very similar or superior in terms of the
number of reversals to failure at mechanical strain amplitudes of 0.2%, 0.3% and 0.4%. In
other words, the three alloys presented practically the same in-phase life at values of
mechanical strain amplitude equal to or higher than 0.2%.
As the graph in Figure 11 indicates, alloy D presented the best performance in in-phase
TMF at all of the applied strain amplitudes. It was thus demonstrated that, among the four
gray cast iron under study, the alloy with the best performance was the one with relatively
low equivalent carbon content and containing the alloying elements chromium and copper.
These conclusions were based on the results of in-phase TMF, where alloy A, albeit devoid
of any special alloying element, presented a behavior similar to that of both alloys C and B,
which are the most alloyed.
Thermomechanical and Isothermal Fatigue Behavior of Gray Cast Iron for Automotive Brake Discs

157
Figure 12 depicts the behavior of the four alloys in thermomechanical out-of-phase fatigue.
Note that in this loading condition, the alloying elements as well as the equivalent carbon
content exerted little or no influence on the low-cycle fatigue strength of the alloys.
10 100 1000 10000
0,1
0,2
0,3
0,4

0,5




2N
f
[cycles]
Δε
m
/ 2 [%]
Alloys
(Out of Phase)
A
B
C
D

Fig. 12. Comparative plot of the mechanical strain amplitude vs. number of reversals to
failure of the four alloys, in TMF out-of-phase.
To facilitate a comparison of the results of the alloys’ behavior in both TMF conditions, they
were plotted in the same figure, but without taking into account the mechanical strain
amplitudes less than 0.2%. This artifice allowed for a clearer view of the performance of the
alloys (Figure 13).
10 100 1000 10000
0,1
0,2
0,3
0,4
0,5

Δε
m
/ 2 [%]
2N
f
[cycles]
Alloys
(In Phase)
A
B
C
D

Alloys
(Out of Phase)
A
B
C
D

Fig. 13. Comparative plot of the mechanical strain amplitude vs. number of reversals to
failure of the four alloys, in-phase and out-of-phase, neglecting amplitudes lower than 0.2%.
New Trends and Developments in Automotive System Engineering

158
Based on the curves in Figure 13, it can be stated that among the low-cycle TMF tests carried
out on specimens of four gray cast iron alloys, the ones performed in the out-of-phase
condition were the most critical, since they led to failure in a lower number of reversals. This

greater severity of the out-of-phase tests is justified by the fact that the tensile stresses in this
test condition are applied at the lowest temperatures of the cycle, in which the material
presents low ductility, thus requiring the application of higher stresses to become strained
than those that would be required to strain it at higher temperatures. The same reasoning
with respect to temperature can be employed to study the behavior of compressive stresses.
The effect of the test condition on the application of stresses is easily observed from the
behavior of the mean stress curves in the low-cycle thermomechanical fatigue tests. These
curves were negative in the in-phase and positive in the out-of-phase condition, as
displayed in Figure 14.
The total strain amplitude that occurs in a TMF test is the sum of the mechanical strain
amplitude, which is predetermined, and the amplitude of thermal strain, which is a function
of the coefficient of thermal expansion of the material and the variation in temperature.
-0,3 -0,2 -0,1 0,0 0,1 0,2 0,3
300
350
400
450
500
550
600


Alloys
A
B
C
D
Temperature [°C]
ε
th

[%]

Fig. 14. Thermal strain presented by alloys A, B, C and D in response to temperature
increase.
Therefore, the value of the percent amplitude of thermal strain employed to obtain the
percent of mechanical strain amplitude for the four alloys of this study in the
thermomechanical fatigue tests was 0.3%.
In order to ascertain whether the IF tests could be adopted, as is normally done, to predict
the alloys’ behavior in TMF, the IF and TMF curves of the four alloys of this study were
plotted on the same graphs of % of total strain amplitude as a function of the number of
reversals. As can be seen in the plots in Figures 15, 16, 17 and 18, when subjected to IF at any
of the temperatures of 25ºC, 300ºC and 600ºC, alloys A, B, C and D presented longer
lifetimes than in out-of-phase TMF, indicating an increase in the severity of the test when
temperature variations occur during cyclic loading.
Thermomechanical and Isothermal Fatigue Behavior of Gray Cast Iron for Automotive Brake Discs

159

10 100 1000 10000
0,1
0,2
0,3
0,4
0,5
0,6



Δε
m

/ 2 [%]
2N
f
[cycles]
Alloy A
In Phase
Out of Phase
25°C
300°C
600°C

Fig. 15. Mechanical strain amplitude as a function of number of reversals to failure for alloy
A. Comparison of in-phase and out-of-phase TMF, and IF at 25ºC, 300ºC and 600ºC.

10 100 1000 10000
0,1
0,2
0,3
0,4
0,5
0,6


Δε
m
/2 [%]
2N
f
[cycles]
Alloy B

In Phase
Out of Phase
25°C
300°C
600°C

Fig. 16. Mechanical strain amplitude as a function of number of reversals to failure for alloy
B. Comparison of in-phase and out-of-phase TMF, and IF at 25ºC, 300ºC and 600ºC
New Trends and Developments in Automotive System Engineering

160

10 100 1000 10000
0,1
0,2
0,3
0,4
0,5
0,6


Δε
m
/ 2 [%]
2N
f
[cycles]
Alloy C
In Phase
Out of Phase

25°C
300°C
600°C

Fig. 17. Mechanical strain amplitude as a function of number of reversals to failure for alloy
C. Comparison of in-phase and out-of-phase TMF, and IF at 25ºC, 300ºC and 600ºC.

10 100 1000 10000
0,1
0,2
0,3
0,4
0,5
0,6


Δε
m
/ 2 [%]
2N
f
[cycles]
Alloy D
In Phase
Out of Phase
25°C
300°C
600°C

Fig. 18. Mechanical strain amplitude as a function of number of reversals to failure for alloy

D. Comparison of in-phase and out-of-phase TMF, and IF at 25ºC, 300ºC and 600ºC.
Thermomechanical and Isothermal Fatigue Behavior of Gray Cast Iron for Automotive Brake Discs

161
As can be seen from the curves, the severity of the tests increases, and hence, the lifetime
decreases in the following sequence: IF at 25ºC, IF at 300ºC, IF at 600ºC and out-of-phase
TMF. This clearly indicates that IF tests are unsuitable to predict thermomechanical fatigue
behavior, at least in the case of the materials of this study.
The precision of the direction to be considered for the in-phase TMF curves, particularly for
alloy D, was impaired because the results of the mechanical strain amplitude of 0.1%, due to
the anomalous results, were not considered. Thus, they were not analyzed from the standpoint
of severity. In general, and apart from anomalies, the smaller the preestablished mechanical
strain the longer the duration of thermomechanical fatigue tests; hence, phenomena such as
creep and oxidation have an opportunity to act, reducing the material’s lifetime.
The gray cast iron alloys that are used in the production of automotive brake discs were
subjected to IF tests because vein graphite behaves like microcracks. Therefore, the conventional
method of calculating the plastic and elastic components of strain cannot be used because it
would yield incorrect values since, depending on the hysteresis, the tensile unloading tangent
could find negative values of plastic strain. Therefore, the extent of hysteresis at half-life was
determined by the mean stress, as shown in Figure 19 [KANDIL, 1999].
Note that the distance db corresponds to the plastic strain amplitude, the horizontal
distance ac corresponds to the total strain amplitude, and the vertical distance ac
corresponds to the stress amplitude; E
1
is the modulus of elasticity in tensile unloading, and
E
2
is the modulus of elasticity in compressive unloading.
The plots of strain amplitude versus number of reversals (Δε
t

x 2N
f
) (Figures 20 to 25)
indicate that the lifes of the alloys under study showed significant differences at 25
o
C, 300
o
C
and 600
o
C. This occurred at all the levels of strain analyzed, i.e., 0.2%, 0.3%, 0.4% and 0.5%,
due to the low ductility of the alloys in question. In these cases, the equivalent carbon (CE)
does not seem to exert any influence on fatigue life at any of the test temperatures.
However, it was found that the life of alloy B increased along with increasing temperature,
which is due to the presence of alloying elements such as molybdenum and chromium,
indicating that these elements increase the materials’ hot mechanical strength.

Fig. 19. Hysteresis curve [KANDIL, 1999].
The alloys with high mechanical strength require greater stresses to become strained.
Therefore, an analysis of the behavior of the alloys of this study based on the plots of stress
New Trends and Developments in Automotive System Engineering

162
amplitude vs. number of reversals (σx 2N
f
) at the temperatures of 25ºC and 300ºC (Figures
20 to 25) indicates that there was no significant decrease in the stress amplitude of the four
alloys. However, when the temperature reaches about 600
o
C (Figure 25), there is a more

pronounced decline in the stress amplitude of the alloys containing little or no
molybdenum, clearly evidencing its relationship with the increase in resistance at high
temperatures. This therefore clearly shows that the alloys most resistant to a decrease in
their mechanical properties in response to temperature, i.e., alloys B, A and D, present a
better performance in terms of the IF lifetime.
10 100 1000 10000
0,002
0,003
0,004
0,005
0,006
0,007
Alloys
A
B
C
D


Δε
T
/ 2 [mm/mm]
2N
f
[cycles]

Fig. 20. IF: Comparative plot of total strain amplitude vs. number of reversals at 25°C.
10 100 1000 10000
0,002
0,003

0,004
0,005
0,006
0,007


Δε
T
/ 2 [mm/mm]
2N
f
[cycles]
Alloys
A
B
C
D

Fig. 21. IF: Comparative plot of total strain amplitude vs. number of reversals at 300°C.
Thermomechanical and Isothermal Fatigue Behavior of Gray Cast Iron for Automotive Brake Discs

163


10 100 1000 10000
0,002
0,003
0,004
0,005
0,006

0,007


Δε
T
/ 2 [mm/mm]
2N
f
[cycles]
Alloys
A
B
C
D


Fig. 22. IF: Comparative plot of total strain amplitude vs. number of reversals at 600°C.

10 100 1000 10000
50
100
150
200
250
300
350
400


Δσ/2 [MPa]

2N
f
[cycles]
Alloys
A
B
C
D


Fig. 23. IF: Comparative plot of stress amplitude vs. number of cycles at 25°C.
New Trends and Developments in Automotive System Engineering

164


10 100 1000 10000
50
100
150
200
250
300
350
400


Δσ/2 [MPa]
2N
f

[cycles]
Alloys
A
B
C
D


Fig. 24. IF: Comparative plot of stress amplitude vs. number of cycles at 300°C.

10 100 1000 10000
50
100
150
200
250
300
350
400


Δσ/2 [MPa]
2N
f
[cycles]
Alloys
A
B
C
D

Fig. 25. IF: Comparative plot of stress amplitude vs. number of cycles at 600°C.
Thermomechanical and Isothermal Fatigue Behavior of Gray Cast Iron for Automotive Brake Discs

165
4. Conclusions
- At in-phase TMF mechanical strain amplitudes of 0.10% the value of fatigue life showed
an anomalous behavior in all the analyzed alloys, which failed prematurely according
to the adopted criterion of a 50% decrease in maximum tensile stress. In other words,
their 2N
f
was lower than that of the highest amplitudes of mechanical strain.
- The in-phase TMF curves indicated that the behavior of the gray cast iron alloys A, B
and C were very similar in terms of 2N
f
at mechanical strain amplitudes of 0.2%, 0.3%
and 0.4%. In other words, the three alloys presented practically the same in-phase TMF
life at mechanical strains equal to or higher than 0.2%.
- The out-of-phase TMF tests were the most critical, leading specimens to failure in a
smaller number of reversals. This greater severity of the out-of-phase tests is explained
by the maximum tensile stresses at the lower temperatures of the cycle.
- The best TMF performance was exhibited by the alloys with relatively low equivalent
carbon content and containing the alloying elements Cr and Cu.
- As for the IF properties, the alloys under study did not show a significant difference at
temperatures of 25ºC, 300ºC and 600ºC, as indicated by the ε – N curves. The CE, was
apparently uncorrelated with the fatigue life.
- Based on the σ – N curves one can see that, even at ambient temperature, there is a
difference among the alloys. With the increase in temperature there is a decline in the
stress amplitude, which is more pronounced in the alloys containing little or no Cr and

Mo. Thus, the alloys with higher mechanical strength require a higher stress to become
strained.
- When subjected to IF at any of the temperatures, 25ºC, 300ºC and 600ºC, the alloys
presented longer lifes and in out-of-phase TMF, revealed an increase in the severity of
the test with the variation in temperature.
- The IF tests were less critical than the out-of-phase TMF tests.
5. References
[1] IOMBRILLER, S. F. “Análise térmica e dinânica do Sistema de Freio a Disco de Veículos
Comerciais Pesados”. Dissertation (doctorate in Mechanical Engineering), São
Carlos: USP – Universidade de São Paulo, p. 177, 2002.
[2] MAZUR, Z., LUNA-RAMÍZES, A., JUÁREZ-ISLAS, J. A., CAMPOS-AMEZCUA, A.
“Failure Analysis of a Gas Turbine Blade made of Inconel 738 LC Alloy”, Engineering
Failures Analysis, Elsevier, V. 12, p. 474 – 486, 2005.
[3] Maluf, O. “Fadiga Termomecânica em ligas de ferro fundido cinzento para discos de
freios automotivos”. PhD. Thesis (doctorate in Science and Materials Engineering),
São Carlos: USP – Universidade de São Paulo, p. 47-130, 2007).
[4] BOIOCCHI, T., “Technological Differences between Tractors, Trailers and Impact in the Safety
and Drivability”, in Colloquium Internacional de Freios, 4, Caxias do Sul, p. 23 – 28,
1999.
[5] WEINTRAUB, M., “Brake additives consultant”, Private Communication, 1998.
[6] HETNARSKI, R. B. “Mechanics and Mathematical Methods – Thermal Stress II”, North-
Holland, Oxford, 2nd Series, V. 2, 1991.
[7] SEHITOGLU, H. “Thermal and thermomechanical fatigue of structural alloys”. In: ASM
HANDBOOK – Fatigue and Fracture. Ohio, V.9, 1996.
New Trends and Developments in Automotive System Engineering

166
[8] COFFIN Jr., L.F., A study of the effects of cyclic thermal stresses on a ductile metal,
Transactions of the ASME, nº 53-A76, 1954, p. 931-949.
[9] HETNARSKI, R. B. “Mechanics and Mathematical Methods – Thermal Stress II”, North-

Holland, Oxford, 2nd Series, V. 2, 1991.
[10] SHI, H-J., KORN, C., PLUVINAGE, G., “High Temperature Isothermal and
Thermomechanical Fatigue on a Molybdenum-Based Alloy”, Materials Science and
Engineering, A247, p. 180 – 186, 1998.
[11] SRINIVASAN, V.S., VALSAN, M., RAO, B. S., MANNAN, S.L., RAJ, B. “Low Cycle
Fatigue and Creep-Fatigue Interaction Behavior of 316L(N) Stainless and Life Prediction by
Artificial Neural Network Approach”, International Journal of Fatigue, V. 25, p. 1327 –
1338, 2003.
[12] ASM International handbook. Heat Resistant Materials, pp. 183-186, 1999.
[13] KANDIL, F.A. Cycle Potential ambiguity in the determination of the plastic strain range
component in LCF testing. International Journal of Fatigue, 21 (1999), 1013-1018.
9
Advanced Robotic Radiative Process Control
for Automotive Coatings
Fan Zeng and Beshah Ayalew
Clemson University - International Center for Automotive Research
United States of America
1. Introduction
In modern automotive manufacturing, coating, drying and curing processes provide essential
protection for car bodies besides decorative functions. However, current coating and curing
processes largely involve the use of convection bake-ovens and contribute immensely to the
energy consumption and greenhouse gas emissions. For example, according to a recent study
(Siewert, 2008), the total energy consumption per car manufactured averages about 3 MW-hr,
of which 1.0-1.4 MW-hr (33-46%) happens in the painting/coating booth. Likewise, of the
nearly 1.1 tons of CO
2
emissions per car manufactured, 0.4 tons (37%) of CO
2
emissions arise in
the painting booths (Prendi et al., 2008). Assuming even the lowest industrial energy costs and

considering the total annual global sales of nearly 70 million cars, estimated energy costs of
painting booth operations alone run into trillions of dollars, not to mention the emission of
tens of millions of tons of CO
2
into the atmosphere.
The energy and environmental issues involved in current automotive coating/paint curing
processes may be alleviated by recent radiation-based methods which use either ultraviolet
(UV) or infrared (IR) radiation to activate/initiate the curing or drying processes (Hagood et
al., 2008) (Vgot, 2007). Compared to convection bake-ovens (Fig. 1a), these radiation-based
methods use less energy, give improved productivity, and produce less air pollutions, such
as CO
2,
volatile organic compounds (VOCs), etc. As an example, a case study reported in
(U.S. Department of Energy, 2003) showed that the replacement of the convection oven by a
new IR oven allowed a metal finishing plant to increase its production by 50% and reduce
natural gas consumption by 25% annually. Another study showed that the implementation

Air

a. Convective Oven b. Fixed Radiant Array c. Robotic Radiant Array
Fig. 1. Alternative automotive paint curing processes
New Trends and Developments in Automotive System Engineering

168
of UV-curable coatings for aluminum can production may save as much as 55% in capital
and installation costs over thermal curing and reduce 47,000 tons / year of CO
2
emission if
implemented industry-wide (U.S. Department of Energy, 1999).
Early applications of radiation-based methods (e.g. UV) in the automotive industry can be

found in curing coated components, such as headlamp lenses, reflectors, instrument panels,
and so on (Starzmann, 2001). The application of UV curing to whole car bodies (clearcoat)
was reported in (Mills, 2001) and (Fey, 2003), in which the coated car bodies were enclosed
and cured by a set of fixed UV lamps with predesigned positions and orientations (Fig. 1b).
Industrial robotic manipulators have also been used in curing automotive parts and whole
car bodies for further improvements in process quality and energy efficiency (Raith et al.,
2001) (Mills, 2005). In these applications, the robotic manipulator is used to move the UV
radiative device (e.g. UV lamp or LED panel attached to the end effector of the robot)
around the target object in a pre-designed path (Fig. 1c). To ensure the curing quality, both
off-line simulations (for process analysis and path design) and online trial tests (for
irradiance measurement and parameter tuning) should be done before the curing system is
implemented in actual production lines (Raith et al., 2001) (Mills, 2005).
However, the open-loop control structure of current robotic UV curing applications,
including the off-line simulations and online trail tests described above, has difficulties in
maintaining the desired quality during actual processes due to the presence of various
disturbances. These include unevenness in UV absorption, geometrical variations, changes
in convective environment etc. In addition, for these open-loop methods, the change in
product shapes and materials not only requires the redesign of the path of the robot
manipulator, but it also causes the repetitive and time-consuming trail tests for calibrating
the curing process.
Compared to typical trial-and-error methods (open-loop), closed-loop control of robotic
actuated processes have been widely used in various industrial applications, such as
welding (Hardt, 1993) (Huissoon et al., 1994) (Moore et al., 1997), painting (Seelinger et al.,
1997) (Omar et al., 2006), spray forming (Jones et al., 2003), and so on. For the robotic UV
curing of automotive coatings discussed in this chapter, the authors have developed some
closed-loop methods, including 1) feedback control through thermal imaging (Zeng &
Ayalew, 2009), 2) online process state and parameter estimation (Zeng & Ayalew, 2010-a),
and 3) multi-variable coordination and optimization (Zeng & Ayalew, 2010-b), in order to
improve the process quality and energy efficiency. These closed-loop control and estimation
methods will be detailed in this chapter.

The rest of the chapter is organized as follows. The second section describes the
fundamental modelling and feedback control design for the robotic UV curing process. The
third section details the design of a state/parameter estimator for online monitoring of the
curing process. This is followed by a section which discusses two fundamental approaches
to achieve optimization of the curing process, and a section that describes a prototype
robotic UV curing system developed for experimental implementation. Finally, the last
section gives the summary and points out future research directions.
2. Process modelling and feedback control design
This section describes the modelling of the robotic UV paint curing process and the design
of a set of closed-loop control strategies through cure-status feedback. Despite the complex
geometries of automotive parts or whole car bodies, the UV lamp/LED moving with the
Advanced Robotic Radiative Process Control for Automotive Coatings

169
robotic end effector only illuminates a small region of the whole target at a certain time and
the dominant radiation usually occurs in the normal direction of that region. Therefore, for
the currently illuminated region, the 3D curing process can be reduced to a 2D problem as
illustrated in Fig. 2. The following subsections detail the modelling of the curing process and
the feedback control design based on this 2D description.

x
y
v
s
θ
r
θ
r
n
s

n
d
0
d
UV Source
Source Path
Target with Paint Film
φ

Fig. 2. The reduced schematic of a robotic UV curing process for a 2D target
2.1 Modeling the robotic UV curing process
In general, the UV curing mechanism can be broken into three coupled physical processes:
irradiation, photo-initiated polymerization, and thermal evolution. Given the 2D schematic
shown in Fig. 2, the mathematical description of the three fundamental processes is detailed
as follows.
2.1.1 Irradiation
The major energy of the UV source is delivered to the target through radiation. The
irradiance (power density) received by the target is strongly determined by the power level
of the UV source and the relative distance and orientation between the source and the target.
In this work, an LED type UV source is selected for its high efficiency and fast on-off
response. As shown in Fig. 2, the LED UV source is composed of a set of small units and
each unit can be modeled as a monochromatic Lambertian point source (Ashdown, 1994).
Since the LED is an incoherent light source, the total irradiance arriving at the target surface
can be obtained by superposition. Given the notations used in Fig. 2, the irradiance
distribution on the target surface is represented by (Modest, 1993):

2
1
()cos ( , ,)cos ( , ,)
(,,) (,)

d( , ,)
=
=
∑
ii
N
sr
i
i
txytxyt
Ixyt kxy
Nxyt
ϕθ θ
π
(1)
where, the spatial coordinates for an arbitrary point on the target surface and the time are
denoted by ( x ,
y
) and t , respectively. The irradiance distribution on the target surface is
represented by
(,,)Ixyt . The number of the LED units and the index of each unit are
denoted by N and i , respectively. The relative distance and orientation between each LED
New Trends and Developments in Automotive System Engineering

170
unit and the target surface are characterized by
d
i
(position vector),
i

s
θ
(emission angle),
and
i
r
θ
(incidence angle). The total power level of the UV LED is represented by the radiant
flux
()t
ϕ
. The coefficient
(,)kxy
is used to model the varying UV absorption throughout
the target surface. It can be observed from equation (1) that the irradiance received by the
target varies with both time and coordinate. This characteristic will also strongly influence
the photo-initiated polymerization and thermal evolution processes to be described later.
2.1.2 Photo-initiated polymerization
Most curing processes involve the polymerization of various monomers. In the UV curing
process, the polymerization is initiated by the UV radiation instead of high temperature. A
typical photo-initiated polymerization is composed of three fundamental phases: initiation,
propagation, and termination. In initiation, the photo-initiators (mixed with the paint)
absorb the UV radiation and create free radicals which initiate the growth of polymer chain.
Propagation follows cross-linking more polymer chains. Termination occurs when growing
chains come together and react to form the dead polymer. Detailed description of the photo-
initiated polymerization can be found in (Hong, 2004) (Goodner, 2002). A simplified kinetic
model is used here to characterize the three fundamental phases of the photo-initiated
polymerization (Hong, 2004).

[](,,)

[ ](,,)(,,)=−
dPI xyt
PI x y t I x y t
dt
φε
(2)

{}{}
0.5 0.5
0.5
0.5
[](,,)
( ) [ ](,,)[ ](,,) (,,)=−
p
t
dM xyt
dt
k
Mxyt PIxyt Ixyt
k
φε
(3)
where, the concentrations of photo-initiator and monomer are denoted by
[]PI and []
M
.
φ

and
ε

represent the quantum of yield for initiation and molar absorptivity, respectively.
The propagation and termination rate constants are denoted by
p
k
and
t
k . It can be seen
from equations (2) and (3) that the spatial distributions of both the photo-initiator and
monomer concentrations are highly influenced by the distribution the UV irradiance.
2.1.3 Thermal evolution
The thermal evolution in the curing process is characterized by the following energy balance
equation:

{} {}
(,,)
[](,,)
(,,) (,,)
∞
=∇ ∇ −Δ − −
dT x y t
c
dt
dM xyt
Tx
y
tH hTx
y
tT
dt
ρ

λ
(4)
In equation (4), the internal energy accumulation (described by the intensity
ρ
, specific heat
capacity
c
, and the change of temperature T ) is determined by the heat conduction
throughout the target (
λ
and
∇
denote the thermal conductivity and the gradient operator,
respectively), the heat generation in the photo-initiated polymerization phase (
ΔH is the
Advanced Robotic Radiative Process Control for Automotive Coatings

171
polymerization enthalpy), and heat convection between the target and the environment ( h
and
∞
T denote the convective heat transfer coefficient and the ambient temperature,
respectively). All radiative heat transfer terms are ignored in this energy balance equation as
they are assumed to be comparatively smaller than the retained terms.
2.2 Feedback control design
Given the system dynamics modeled in subsection 2.1, the objective of the feedback control
design is to take some of those measurable process outputs as feedback and manipulate the
radiant source (either in motion or power) so that the desired process quality set-point can
be achieved. In the present case, since the cure-conversion level (normalized monomer
concentration) is usually difficult to measure directly, the temperature, which is highly

correlated to the cure-conversion, can be used to provide on-going curing status information
for the controller. The temperature can be measured through one or more infrared (IR)
cameras. The following paragraphs will detail the use of temperature feedback and the
corresponding feedback control design.
2.2.1 Temperature feedback through infrared (IR) cameras
The principle of temperature measurement through IR cameras is a form of thermal
imaging, in which the IR camera captures the images of the target in the infrared frequency
domain and correlates them to the temperature distribution of the target based on
fundamental radiative heat transfer theory. Three possible configurations (as shown in
Fig.3) can be used to implement online temperature measurement through IR cameras for
the purpose of robotic process control.

v
a. Local IR
v
b. Global IR
v
c. Hybrid Configuration

Fig. 3. Alternative temperature measurement configurations through IR cameras
In the local IR configuration (Fig. 3a), the IR camera is co-located with the moving radiant
source, so it mainly focuses on the area which is currently being cured. This configuration is
simple and effective for local temperature measurement. In the global IR configuration, the
IR camera is fixed to the global coordinate system (e.g. test bench) so that it can have a full
view of the target. With this configuration, the controller can receive more information from
the IR camera (e.g. the complete temperature map of the target), but it also increases the
image processing complexity. The hybrid configuration combines both the advantages of
both the local and global ones, and it can help achieve better control performance with
moderate cost compromise. The authors have developed different feedback control
strategies for these alternative temperature measurement configurations, and the following

subsection will give an overview of these strategies.