A NEW PARADIGM FOR AUTOMOTIVE MASS BENCHMARKING
September 2015
© WorldAutoSteel 2015
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Table of contents
(Click to navigate)
Page
1.0 Introduction
1
1.1 Study Scope
2
1.1.1 Mass Benchmarking Methodology
2
1.1.2 Vehicle Types Included
5
1.1.3 Cost References
6
1.1.4 Life Cycle Assessment
6
2.0 Automotive Mass Benchmarking – Key Findings
2.1 Mass efficiency of today’s Steel Designs Vary Drastically – Average and Non-Optimized Steel
vs. Steel Efficient Designs
7
7
2.1.1 Subsystem Examples
7
2.1.1.1 Front Door
7
2.1.1.2 Front Bumper
9
2.1.1.3 Body Structure
11
2.1.2 All Subsystems Comparison Table
13
2.2 When Compared to an Efficient Steel Design, the Mass Savings Gap with Aluminium
Significantly Reduces
14
2.2.2 Subsystem Examples
14
2.2.2.1 Front Door
14
2.2.2.2 Front Bumper
16
2.2.2.3 Body Structure
18
2.2.3 Summary of Subsystems
2.3 Mass Savings Achieved at the Component Level Often Not Realized at the System Level
20
21
2.3.1 Subsystem Examples
21
2.3.1.1 Front Door
21
2.3.1.2 Front Bumper
22
2.3.2 Summary of Subsystems
23
2.4 There Is A Narrow Margin In Vehicle Curb Weights Between Vehicles Using Efficient Stee
Body Structures And Aluminium Body Structures
© WorldAutoSteel 2015
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i
2.5 There is Yet Untapped Mass Savings Potential for Steel
25
2.5.1 FutureSteelVehicle Body Structure
25
2.5.2 Steel Member Company Examples
25
3.0 The Cost of Lightweighting
3.1 Subsystem Examples
26
26
3.1.1 Body Structure
26
3.1.2 Door Structure
26
3.1.3 Hood Structure
26
3.2 Relationship Between Cost and Fuel Efficiency
27
3.3 Summary
28
4.0 Life Cycle Assessment
29
4.1 Model Parameters
29
4.1.1 Body Structure Mass
29
4.1.2 Bill of Materials (BOM) Calculations
30
4.2 Body Structure Results
31
4.2.1 Total Life Cycle GHG Emissions
31
4.2.2 Body Structure GHG Emissions by Life Cycle Phase
31
4.3 Other Systems
34
4.3.1 Subsystem Masses
34
4.3.2 LCA Results
35
5.0 Conclusions
5.1 Final Observations on the Power of Statistical Benchmarking as a Tool for Mass Efficiency
36
37
Annotations
38
Appendix 1 – Model Equations
39
© WorldAutoSteel 2015
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1.0 Introduction
The increasing demand for automotive fuel efficiency and mass reduction has resulted in increased use of
alternative materials in the design of various components that have historically been produced using steel.
Mass benchmarking often is done with a one-at-a-time approach. A reference vehicle is selected, the
vehicle is disassembled, parts weighed and analyzed, and then the data used to set mass targets for a
vehicle under design. However, a benchmarking study results, commissioned by WorldAutoSteel and the
Steel Market Development Institute (SMDI) and conducted by EDAG Int’l, Inc., point to a powerful new
statistics-based benchmarking methodology.
Rather than considering a single vehicle or a small set of vehicles, this method looks at a very large sample
of vehicles over a range of sizes and segments. From this larger population, assumptions on mass drivers
and their influence on real vehicles may be tested via statistical methods. An automotive designer can then
look at subsystems which are much lighter than the ‘average’ vehicle, and therefore set subsystem targets
on a more accurate basis than that which is being accomplished in the industry today.
The findings of the study, which used the methodology to study automotive closures, were surprising and
put single-point mass studies into context with the reality of what is achieved in current vehicles. The
findings can be summarized in the following statements:
1. Mass efficiency of today’s steel designs vary drastically. When comparing some steel
components of the same size and function, there are drastic differences in the range of weights in
what should be similar mass subsystems. In fact, some steel designs of the same size,
performance and similar segment are nearly twice as heavy as others. There is a great deal of
untapped opportunity in current production vehicles for mass reduction, even with the technology
and materials already in use.
2. When compared to an efficient steel design, the mass savings gap with aluminium
significantly reduces. Statistical evaluation conducted in the study identified those components
that are most mass efficient. When the efficient steel designs were compared to the aluminium
designs in the study sample, the mass savings achieved was greatly reduced, and in some cases,
resulted in a mass increase for aluminium compared to steel.
3. Mass savings achieved at the component level are often not realized at the system level.
While this study did not investigate the reason for this loss of mass advantage, it is clear that in
nearly every component reviewed, the mass savings that was achieved at the component structure
level was lost along the design development process. Is the structure mass savings causing the
addition of other, heavier features to the system? Are other elements of the system not downsized
to adjust to the lighter weight? Is the goal for mass savings simply to allow inclusion of other heavier
features? These are unanswered questions about which we hope the results of this study will spur
further discussion.
4. There is a narrow margin in vehicle curb weights (CVW) between vehicles with steel
structures and those with aluminium structures. The data show that while the state-of-the-art
of the aluminum body structures in the database reduce vehicle curb weight by 9.3% compared to
average steel structures, current efficient steel structures reduce vehicle curb weight by 6.5%
compared to average steel structures, closing the gap with aluminium to just 2.8%.
5. There is yet untapped mass savings potential for steel. Current applications do not take
advantage of the full portfolio of steel grades with the newest GigaPascal strength steels that also
increase ductility and flexibility. Steel industry application demonstrations, which use a broader
portfolio of steel grades than seen in today’s production designs, have demonstrated greater mass
reduction potential than currently achieved.
© WorldAutoSteel 2015
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Two other important dimensions are also addressed in this study – costs and environmental performance.
Cost: Reference examples of subsystem cost comparisons taken from other studies were used to illustrate
the cost of the lightweighting achieved.
Environmental performance: A separate Life Cycle Assessment LCA) was conducted on several key
components to compare emissions savings achieved.
The following report details the findings and brings into sharp focus the gap between current lightweighting
efforts and their impact on vehicle mass and environmental efficiency and the need to include this statistical
methodology to develop design mass targets.
1.1
Study Scope
The study investigated mass efficiency for the vehicle subsystems shown in Table 1.1-1.
Table 1.1-1: Vehicle Subsystems Included in the Study
a.
b.
c.
d.
e.
Front door frame
Hood
Hatchback
Deck lid
Lift gate
f. Wheels
g. Instrument panel beam
h. Front bumper beam
i. Rear bumper beam
j. Body structure
The study included the following scope of work for each of the identified subsystems.
A. The mass statistics including mean, standard deviation, minimum and maximum.
B. Compare and contrast the “trend-lines” of the material usage and mass efficiency of these more
recent vehicle systems to those of the 2010 report.
C. Update the insight and conclusions into the mass drivers of each subsystem.
D. Identify the subsystems with exceptional mass efficiency, and identify the effect that material
selection has on this efficiency.
The mass data was taken from the A2Mac1 European and North American tear-down databases. The
method employed looks at a large sample of vehicles (240) over a range of sizes, segments and markets.
From this larger population the subsystems which are much lighter ‘mass efficient’ than the ‘average’
vehicle were determined, after adjusting for the system attributes.
1.1.1
Mass Benchmarking Methodology
The methodology followed in this study is consistent with a Society of Automotive Engineers paper
published in 2015 by Dr. Don Malen, University of Michigan, and Jason Hughes, A2Mac1.1 Figure 1.1-1
provides a summary of the steps in the process.
© WorldAutoSteel 2015
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Figure 1.1-1: Steps in the Statistical Benchmarking Process as Detailed in the
Referenced SAE Paper
The analysis described in this WorldAutoSteel report used the Regression models identified in the SAE
paper to examine the database and draw conclusions. This Statistical regression analysis (Regression
Process in the diagram) was used to fit both a linear equation and a power equation to the various
components’ attributes. The linear model was first determined retaining the statistically significant
attributes, and then the same retained attributes were used for the power model.
The generic forms of the model equations used were as follows. The specific equation used for each
component is provided in Appendix 1.
Linear models were of the form:
ḿ
⋯
Where ḿ is the subsystem nominal mass for the full set of vehicles considered. Some of the attributes were
continuous variables (gross vehicle weight, for example), some were categorical attributes (construction A,
construction B, or construction C), and others were a binary attribute (side air bag: yes/no).
After determining significant attributes using the linear model, a power model was fit of the form:
ḿ
…
and was used for comparing mass performance of competitive material designs.
To determine a model for “efficient” designs, the power model equation was modified by varying the
number (defined as “n” value) of standard errors below the mean, keeping at least three data points
below the curve:
ḿ
…
Where:
ḿ EFF = predicted mass for mass efficient designs
r = standard error factor determined by the regression
n = number of standard errors below the mean for which at least three samples were observed
© WorldAutoSteel 2015
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Figure 1.1-2, a plot of the actual mass value versus the primary mass driver, shows the average and
efficient model equations for each material.
Figure 1.1-2: Example Plot – Actual Mass Value vs. Primary Mass Driver
Mass efficient components were identified by calculating the estimated mass using the linear model
equation (using separate equations for steel and for aluminium) and by plotting the actual measured mass
versus the estimated mass for each component, as show in Figure 1.1-3. The solid line represents cases
where actual and estimated masses are equal (i.e. ‘average’). Those door frames above the solid line
(where actual is greater than estimated) are heavier than ‘average’ whereas those below the solid line
represent door frames lighter than the ‘average’ Subsystems which are much lighter than the ‘average’
vehicle (those that fall at least 1 standard deviation below the curve) are considered to be mass efficient.
Figure 1.1-3: Example Plot – Actual Measured Mass vs. Estimated Component Mass
Functional Equivalence / Performance Criteria: Within this mass benchmarking methodology, there
may be questions about whether mass efficient components meet functional market performance
requirements and therefore are not lighter weight because of compromises in performance. A separate
© WorldAutoSteel 2015
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door study sponsored by SMDI and conducted by EDAG3 verified that door structures, as one prime
example, meet market performance criteria and that performance differences are not generally an
explanation for differences in mass efficiency. Additionally, this statistical methodology minimizes the effect
of a few outlier points in relation to the bulk of the data set points.
1.1.2
Vehicle Types Included
As of July 2012 the A2Mac1 European database contained 172 vehicles and the North American database
contains 24 vehicles. The number of vehicles per production year is shown in Figure 1.1-4. The types of
vehicles in the total data sample are shown in Figures 1.1-5. For the new data set, the vehicle destination
market was determined to be 42 to North/South America, 64 to Europe/United Kingdom, and 4 to Pacific
Rim/Asia. These destination market figures do not reflect the distribution of vehicle production locations.
The combined A2Mac1 database contains a broad representation of global automotive manufacturers.
40
NUMBER OF VEHICLES
35
30
25
20
15
10
5
0
2000200120022003200420052006200720082009201020112012
VEHICLE PRODUCTION YEAR
NUMBER OF VEHICLES
Figure 1.1-4: Number of Vehicles per Production Year in Total Data Sample
100
90
80
70
60
50
40
30
20
10
0
Van
SUV
Sedan
Hatchback
Light Duty
Truck
VEHICLE TYPES
Figure 1.1-5: Vehicles Types in Total Data Sample
© WorldAutoSteel 2015
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1.1.3
Cost References
This report focuses on mass benchmarking. In order to provide direct cost comparison data for the
subsystems studied, hardware tear-down and engineering analysis cost study of representative
subsystems would be necessary (but, was not part of this study’s work scope). However, for the purpose
of this report, subsystem cost comparisons relevant to this Auto Mass Benchmarking study were taken from
other studies as references. These reference examples illustrate (Section 3.0) typical cost comparison data.
1.1.4
Life Cycle Assessment
Life Cycle Assessment (LCA) is a methodology that considers a vehicle’s entire life cycle, from the
manufacturing phase (including material production and vehicle assembly) through the use phase
(including production and combustion of fuel) to the end of life (EOL) phase (including end of life disposal
and recycling).
Current automotive emissions regulations around the world are aimed at reducing Greenhouse Gas (GHG)
emissions of automobiles, but focus only on tailpipe emissions, which are only a portion of the actual lifecycle impact of an automobile (Figure 1.1-6).
Emphasis on the tailpipe
alone may have the
unintended consequence of
increasing GHG emissions
during the vehicle life. For
example,
many
automakers, in order to
comply with increasingly
stringent tailpipe emissions
regulations, are turning to
low- density materials in an
effort to reduce mass. By
reducing the mass of a
vehicle, it is possible to
reduce
the
fuel
consumption
and,
Figure 1.1-6: Sources of GHG Emissions In A Vehicle's Life Cycle
consequently, the tailpipe
emissions. However, many of these materials can have impacts in the other life cycle phases that outweigh
any advantage that may be gained in the use phase. This means that, contrary to the stated objective of
reducing the GHG emissions of automobiles, tailpipe-only regulations may have the unintended
consequence of actually increasing the GHG impact. This is why WorldAutoSteel is participating in the
development of LCA tools and methodology and encouraging the use of LCA in the formulation and
implementation of automotive emissions regulations.
Section 4.0 contains an LCA study based on the EDAG A2Mac1 benchmarking study results. As with the
FutureSteelVehicle (FSV) program2, the LCA work was conducted for key subsystems (body structure, front
bumper, rear bumper, wheels, hatchback, hood, front door) using the University of California at Santa
Barbara (UCSB), Bren School of Environmental Management’s Automotive Materials Greenhouse Gas
(GHG) Comparison Model4, whose methodology has been peer-reviewed and approved according to ISO
14040:2006. Specific parameters and methodology are outlined in Section 4.0.
© WorldAutoSteel 2015
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2.0 Automotive Mass Benchmarking – Key Study Findings
2.1
Mass efficiency of today’s Steel Designs Vary Drastically – Average and
Non-Optimized Steel vs. Steel Efficient Designs
As the data was investigated during this study, it became clear that all steel components are not created
equally. For instance, there are many levels of efficiency in the sample among the steel doors, with some
doors of similar segment class and performance weighing twice as much as others. There are similar
examples among some of the other components, which indicate that there is much room for improvement
and optimization among the current production steel component structures. Following are examples
comparing the average versus efficient mass as well as the non-optimized mass (defined as the
approximate heaviest example considering the same mass drivers) of the steel component structures in
the data.
2.1.1
Subsystem Examples
2.1.1.1 Front Door
The front door system is the complete door assembly inclusive of intrusion beam, glass, linkages, trim, lock
and all mounting hardware. The door frame consists of the door frame welded assembly: door inner and
outer, window frame, door beam, and all welded reinforcements. For all the doors in the sample (219), the
dimensions shown in Figure 2.1-1 were recorded. Table 2.1-1 provides example data.
Figure 2.1-1: Front Door Dimensions
Table 2.1-1: Example of Data Collected for the Front Door
Height
(mm)
Area
(length
x
beltline
height +
top
triangular)
(m2)
Tumble
home
(mm)
1167.00
1163.0
1.081
1248.0
1100.0
1.373
Front
Door
Frame
(kg)
Front
Door
Frame
Material:
1= Steel
2= Alum
3=Mag
4= Others
Front
Door
Total
(kg)
Front
Door
Glass
(kg)
Length
(mm)
12.91
1
26.40
3.16
16.27
1
32.79
3.11
© WorldAutoSteel 2015
Hinge
Span
(mm)
Window
Regulator
Type:
1= Cable
2= Linkage
3= Print
Window
Frame
Type:
1= Rear of A
2=
Overlapping
3= Frameless
245.0
388.0
3
1
254.0
447.0
3
1
7
The statistical data for the door frame weights and the number of vehicles are shown in Table 2.1-2.
Table 2.1-2: Front Door Frame Weights
Mass (kg)
Door Frame
Material
Nr
Steel
Aluminium
Mean
St Dev
Min
Max
203
17.01
2.70
9.85
27.20
16
11.71
1.77
9.23
15.54
A significant mass driver for the door frame was found to be the side view area, the material of construction
and, to a lesser degree, the window regulator type.
Figure 2.1-2 illustrates average door mass and efficient door mass plus one of the heaviest (non-optimized)
doors for the specified area of 1.1m^2. Table 2.1-3 shows that the non-optimized door is +23% heavier
than the average steel door. The efficient steel door, among the lightest according to the regression
analysis, saves -21% mass compared to the overall average and a full -35% over the non-optimized
example.
Figure 2.1-2: Door Frame Comparison
Average vs. Efficient and Heaviest (Non-Optimized) Door with 1.1 m^2 area
Table 2.1-3 Front Door Frame Material Comparisons
Comparison Steel Average to
Steel Efficient Designs
Frame
Mass
Mass (kg)
Difference
Steel Average
16.3
Steel Non-Optimized
19.9
+ 23%
Steel Efficient
12.9
- 21%
For door with 1.1 m^2 area
© WorldAutoSteel 2015
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2.1.1.2 Front Bumper
The front bumper system is the complete bumper assembly inclusive of fascia, energy absorbing foam and
all mounting hardware. The bumper beam consists of the bumper beam welded assembly, beam and crash
cans and all welded on reinforcements, Figure 2.1-3. For all the bumper systems in the sample (222) the
data shown in Table 2.1-4 was recorded.
Figure 2.1-3: Front Bumper System
Table 2.1-4: Example of Collected Data for the Front Bumper Beam
Front
Bumper
Mass Total
(kg)
Front
Bumper
Beam
Mass (kg)
Beam
Mat:
1 = Stee
2=Alum
3=Mag
4=Plasti
c
Manufacturing
Method:
1=Extrusion
2=Stamped
3=Roll Form
4=Hydroform
5=Hot Stamp
Crush
Cans:
1=Yes
2=No
Bumper
Length
(mm)
Distance
Between
Rails (mm)
Vehicle
Type:
1=Utility:
CVW Curb pick up &
SUV,
Vehicle
Weight(kg) 2=Passeng
er: sedan,
Hatchback
& Others
Destination
Marke:
1 = North
America
2 = Europe UK
3 = Pacific
Rim - Asia
15.36
3.70
2
1
1
1204.0
1026.0
1656
2
1
17.19
4.07
2
1
1
1180.0
1000.0
1328
2
2
The statistical data for the beam weights and the number of vehicles versus beam weights are shown in
Table 2.1-5.
Table 2.1-5: Example of Data Collected for the Front Bumper Beam Weights
Mass (kg)
Front Bumper Beam
Nr
Mean
St Dev
Min
Max
Steel
150
7.31
3.08
2.26
28.19
Aluminium
72
4.89
1.51
1.45
9.23
A significant mass driver for the front bumper beam was the vehicle curb weight (CVW), construction
material steel or aluminium, and width of the mounting rails. A notable example of the need for optimization
of current steel production components can be seen with the front bumper, though the data is similar for
the rear bumper as well. The non-optimized steel bumper (approximated in Figure 2.1-4) is nearly double
(+89%) the weight of the average bumper in the same CVW of 1500 kg (Table 2-1-6). The steel efficient
bumper saves -47% mass over the average.
© WorldAutoSteel 2015
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Figure 2.1-4: Front Bumper Frame Comparison
Average vs. Efficient and Heaviest (Non-Optimized) Bumper CVW 1500 kg, 982 mm
Table 2.1-6 Front Bumper Frame Material Comparison
Comparison – Steel Average, Efficient and NonOptimized
Bumper
Mass
Mass (kg)
Difference
Steel Average
6.3
Steel Non-Optimized
11.1
+ 89%
Steel Efficient
3.3
- 47%
For CVW 1500kg, Rail Width 982mm
© WorldAutoSteel 2015
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2.1.1.3 Body Structure
The body structure analyzed is the complete body assembly inclusive of paint, sealer and the engine cradle
as shown in Figure 2.1-5.
Figure 2.1-5: Body Structure and Engine Cradle
Of the 240 vehicles, suitable data for the body structure was available for 217 vehicles, 207 constructed
from steel, four from aluminium and six mainly steel but with some panels made from aluminium. The
statistical data for the structure weights and the number of vehicles are shown in Table 2-1.7.
Table 2.1-7: Body Structure Weights
Mass (kg)
Body Structure
Material
Nr
Mean
St Dev
Min
Max
Steel
207
334.9
72.3
159.5
665.9
Aluminium
4
247.3
68.8
144.4
289.1
Steel/Aluminium
6
389.6
64.5
301.6
465.2
In order to normalize the mass of the body structure to its size, for all the body structures in the sample
(217) the data shown in Table 2.1-8 was collected.
Table 2.1-8: Example of Collected Data for Body Structure
Body Structure
Body
+ Engine
Structure
Cradle Mass
Mass (kg)
Total (kg)
Body
Material:
1 = Steel
2=Alum
3=Mag
4=Plastic
5=Steel Alloy
Vehicle Type:
1=Utility: pick up &
GVW (Gross
SUV
Vehicle
2=Passenger:
Weight) kg
sedan, Hatchback
& Others
Destination
Market:
1 = North
America
2 = Europe - UK
3 = Pacific Rim Asia
Drive Config:
1 = FWD
Plan View
2 = RWD
Area (m^2)
3 = AWD
4 = 4WD
366.8
349.4
5
2259
2
2
3
9.496
356.4
339.0
5
2123
2
2
1
9.211
Significant mass drivers identified for the body structure were gross vehicle weight (GVW), the plan view
area of the vehicle (length x width) and the material used for construction. The average curves are plotted
for incremental plan view areas since both GVW and plan view area are mass drivers for body structures.
© WorldAutoSteel 2015
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Figure 2.1-6 and Table 2.1-9 provide this comparison for body structures. The smaller difference among
the average, non-optimized and steel efficient may be indicative of the industry’s efforts to reduce vehicle
weight and what is still left to be done. Included in this figure and table is the fully optimized, lightweight
FSV, which includes a high AHSS body structure content (95%). FSV and other concept projects (see
examples in Section 2.5) note opportunities for more mass reduction with advanced steels and steel
technologies.
Figure 2.1-6: Body Structure Comparison
Average vs. Efficient and Heaviest (Non-Optimized) Body Structure with GVW 1928 kg, Area 8.75 m2
Table 2.1-9: Body Structure Material Comparison
Comparison Steel Average to
Steel Efficient Designs
Structure
Mass
Mass (kg)
Difference
Steel Average
348.3
Steel Non-Optimized
385.0
+ 10%
Steel Efficient
305.7
- 12%
FSV AHSS
286.6
- 18%
GVW 1928kg & Plan Area 8.75 m2
© WorldAutoSteel 2015
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2.1.2
All Subsystems Comparison Table
Table 2.1-10 provides the data for mid-size vehicle steel componentry currently on the road today,
comparing the average steel designs to the most efficient in each mass driver. It provides an overview of
the opportunities that still exist to employ AHSS and design optimization to obtain greater, more cost
effective mass reduction.
Table 2.1-10: Mass saving potential - Average Steel vs. Efficient Steel - Structure Only
Mid-Size Vehicle
Vehicle Subsystem
Estimated Mass Normalized Designs
Mass Driver Values
2
Average
Efficient
Steel
Steel
kg
16.3
kg
12.9
%
-21%
Difference
Front Doors
Area = 1.1 m
Hood
Area = 1.68 m2
13.5
10.4
-23%
Hatchback
2
Area = 1.23 m & 444mm depth
11.4
8.7
-24%
Decklid
Area = 1.34 m2
10.7
8.9
-17%
Liftgate
Area = 2.11 m
2
15.3
12.2
-20%
Wheel Rim
Dia = 415mm & Width = 184mm
9.2
7.2
-22%
Front Bumper
CVW 1500kg, Rail Width 982mm
6.3
3.3
-47%
Rear Bumper
CVW 1500kg
6.2
2.7
-57%
Body Structure
GVW 1928kg & Plan Area 8.75 m2
348.3
305.7
-12%
Body Structure – FSV-AHSS
GVW 1928kg & Plan Area 8.75 m2
286.6
-18%
Note: Structure mass based on power regression equations
© WorldAutoSteel 2015
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2.2
When Compared to an Efficient Steel Design, the Mass Savings Gap with
Aluminium Significantly Reduces
Aluminium material substitution for steel is often credited with as much as 40% mass savings. This could
be true if the comparison is made with non-optimized, inefficient steel designs. What is the reality of mass
savings achieved when comparisons are made to the spectrum of vehicles in this database? The following
subsystem examples address that question.
2.2.2
Subsystem Examples
2.2.2.1 Front Door
Figure 2.2-1 illustrates the relationship of the door frame mass to side view area. Appendix 1.A. provides
the equations used to identify the expected ‘average’ for steel and aluminium door frames, as well as the
mass estimates for the ‘efficient’ door frame and corresponding “n” values.
Figure 2.2-1: Front Door Frame Mass vs. Area of Door Frame (Power Estimation Models)
Table 2.2-1 provides the estimated masses for a door frame with a side view area of 1.1m2. The results
indicate the average aluminium door frame is 30% lighter than the average steel. However, when the steel
design is an optimized, fully efficient one, the mass savings potential for aluminium is reduced to 22% (2.8
kg per door), assuming that the aluminium door is also an efficient design. However, the average door
among the aluminium designs, those whose weight represents the more typical masses seen in production
today, the mass savings is reduced to 1.6 kg per door or just 12%.
Table 2.2-1 Front Door Frame Material Comparisons
Comparison Steel Average to
Aluminium Average Designs
Mass Reduction
Frame
Mass (kg)
%
Delta (kg)
Steel Average
Alum Average
© WorldAutoSteel 2015
16.3
11.3
-30%
Comparison Steel Efficient to
Aluminium Efficient Designs
Frame
Mass (kg)
Mass Reduction
%
Delta (kg)
Steel Efficient
Alum Efficient
12.9
10.1
-22%
2.8
Alum Average
For door with 1.1 m^2 area
11.3
-12%
1.6
5.0
14
Figure 2.2-2 is a parity plot of actual vs. estimated masses for each door frame. The solid line represents
cases where actual and estimated masses are equal (i.e. ‘average’). Those door frames above the solid
line (where actual is greater than estimated) are heavier than ‘average’ whereas those below the solid line
represent door frames lighter than the ‘average’. Highlighted on this graph in green are the steel door
frames which were determined to be most mass efficient based on the linear regression model.
Figure 2.2-2: Front Door Frame Mass Efficient Designs (Linear Estimation Models)
OEM Data
As an example, included in Figures 2.2-3 and 2.2-4 are graphs highlighting the doors for one particular, but
unidentified, OEM. From the charts, it can be seen that some of this OEM’s doors are efficient and others
are not. This type of data can provide a unique comparison for OEMs to identify the outliers in efficiency
compared to other current production vehicles.
Figure 2.2-3: OEM Example, Mass vs. Area Comparison
© WorldAutoSteel 2015
Figure 2.2-4: OEM Example, Estimated vs. Actual Comparison
15
2.2.2.2 Front Bumper
Figure 2.2-5 illustrates the relationship of the bumper beam mass to the vehicle curb weight (CVW).
Appendix 1.G. provides the front bumper beam equations.
Figure 2.2-5: Front Bumper Mass vs. Area (Power estimation models)
Table 2.2-2 shows the estimated masses for the bumper beam for CVW of 1500 kg and rail mounting width
of 982 mm. The results indicate a mass saving of 33% for the average values for aluminium versus steel.
The mass potential of aluminium is reduced to 11% (0.4 kg per beam) when comparing the ‘efficient’
designs of both materials. When compared to a steel efficient design, an average aluminium bumper
increases component mass by +26% (+0.9 kg).
Table 2.2-2: Front Bumper Material Comparison
Comparison Steel Average to Aluminium
Average Designs
Mass
Reduction
Frame
Material Option
Mass (kg)
%
Delta
Comparison Steel Efficient to Aluminium
Designs
Mass
Reduction
Frame
Material Option
Mass (kg)
%
Delta
Steel Average
6.3
Steel Efficient
Alum Average
4.2
-33%
2.1
3.3
Alum Efficient
3.0
-11%
0.4
Alum Average
4.2
+ 26%
+ 0.9
For CVW 1500 kg, Average Rail Width 982 mm
© WorldAutoSteel 2015
16
Figure 2.2-6 is a parity plot of the actual versus estimated masses for front bumper beams. Bumper beams
above the solid line are heavier than ‘average’ whereas those below the solid line represent bumper beams
lighter than the ‘average’. Highlighted on this graph in green are steel front bumpers beams which are
exceptionally lighter.
Figure 2-2.6: Front Bumper Beam Mass Efficient Designs (Linear estimation model)
OEM Data
Figures 2.2-7 and 2.2-8 are graphs indicating the front bumpers for another unidentified, OEM. Note again
that there are those examples within the same OEM brand that are considered efficient designs and those
that are not.
Figure 2.2-7: OEM Example, Mass
vs. Curb Mass Comparison
© WorldAutoSteel 2015
Figure 2.2-8: OEM Example, Estimated
vs. Actual Comparison
17
2.2.2.3 Body Structure
Figure 2.2-9 illustrates the relationship of the body structure mass to Gross Vehicle Weight (GVW). The
average curves are plotted for incremental plan view areas since both GVW and plan view area are mass
drivers for body structures.
Figure 2.2-9: Body Structure Mass vs. GVW and Area (Power estimation models)
Table 2.2-3 shows the estimated masses for a typical mid-size sedan body structure with GVW of 1928 kg
and plan view area of 8.75 m². The results indicate a mass saving of 31% for the average values for
aluminium versus steel. The mass potential of aluminium is reduced to 16% when comparing the ‘efficient’
designs of aluminium with FSV AHSS structures. Due to the limited data points for aluminium body
structures, no differentiation was made between average and efficient aluminium structures.
Table 2.2-3: Body Structure Material Comparison
Body Material Options
Body & Engine Cradle
Mass (kg)
Mass Reduction
%
Delta (kg)
Steel Average
348.3
Steel - Alum
329.9
-5%
18.4
Steel Efficient
305.7
-12%
42.5
FSV AHSS
286.6
-18%
61.7
240.7
-31%
107.5
Compared to FSV
-16%
45.9
Aluminium
Plan View Area: 8.75 m^2
GVW: 1928 kg (Mid Size Sedan)
© WorldAutoSteel 2015
18
Figure 2.2-10 is a parity plot of the actual versus estimated masses for body structures. The solid line
represents cases where actual and estimated masses are equal (i.e. ‘average’). Body structures above the
solid line are heavier than ‘average’ whereas. The body structures below the ‘estimated’ equals ‘actual’
line represent body structures lighter than the ‘average’.
Highlighted on this graph are green circle points for steel body structures which are exceptionally lighter
`(efficient). The green triangular points on the graph are the FSV body structure points. The red square
points identify aluminium body structures.
Figure 2.2-10: Body Structure Mass Efficient Designs (Linear estimation models)
OEM Data
Figures 2.2-11 and 2.2-12 include graphs indicating the body structures for one particular, but unidentified,
OEM.
Figure 2.2-11: OEM Example, Mass vs. GVW Comparison
© WorldAutoSteel 2015
Figure 2.2-12: OEM Example, Estimated vs. Actual Comparison
19
2.2.3
Summary of Subsystems
The summary of results in Tables 2.2-4 and 2.2-5 shows that the mass saving potential of aluminium is
significantly reduced when compared with ‘efficient’ steel designs.
Table 2.2-4: Mass saving potential - Average Steel vs. Average Aluminium - Structure Only
Mid-Size Vehicle
Vehicle Subsystem
Estimated Mass Normalized Designs
Mass Driver Values
2
Average
Average
Steel
Aluminium
kg
kg
%
16.3
11.3
-30%
Difference
Front Doors
Area = 1.1 m
Hood
Area = 1.68 m2
13.5
8.1
-40%
Hatchback
Area = 1.23 m2 & 444mm depth
11.4
8.1
-29%
Area = 1.34 m
2
10.7
8.1
-24%
Liftgate
Area = 2.11 m
2
15.3
10.2
-33%
Wheel Rim
Dia = 415mm & Width = 184mm
9.2
8.3
-10%
Front Bumper
CVW 1500kg, Rail Width 982mm
6.3
4.2
-33%
Rear Bumper
CVW 1500kg
6.2
4.3
-31%
Body Structure
GVW 1928kg & Plan Area 8.75 m2
348.3
240.7
-31%
Decklid
Note: Structure mass based on power regression equations
Table 2.2-5: Mass saving potential - Efficient Steel vs. Efficient Aluminium - Structure Only
Mid-Size Vehicle
Vehicle Subsystem
Estimated Mass Normalized Designs
Mass Driver Values
Front Doors
Area = 1.1 m2
Hood
Area = 1.68 m2
Efficient
Efficient
Steel
Aluminium
kg
kg
%
12.9
10.1
-22%
Difference
10.4
6.9
-34%
2
8.7
7.6
-13%
Area = 1.34 m
2
8.9
7.8
-11%
Liftgate
Area = 2.11 m
2
12.2
10.2
-16%
Wheel Rim
Dia = 415mm & Width = 184mm
7.2
6.4
-12%
Front Bumper
CVW 1500kg, Rail Width 982mm
3.3
3
-11%
Rear Bumper
CVW 1500kg
Hatchback
Decklid
Body Structure
Body Structure – FSV-AHSS
Area = 1.23 m & 444mm depth
2.7
2.1
-22%
GVW 1928kg & Plan Area 8.75 m
2
305.7
240.7*
-21%
GVW 1928kg & Plan Area 8.75 m
2
286.6
240.7*
-16%
Note: Structure mass based on power regression equations
* Due to limited data points for aluminium body structures, no differentiation was made between average and efficient aluminium
structures.
© WorldAutoSteel 2015
20
2.3
Mass Savings Achieved at the Component Level Often Not Realized at the
System Level
The following subsystem examples and summary table provide insight on the mass reduction achieved at
the component structure level, e.g., a door frame assembly, compared to the mass of the total system
assembly. In many of the systems studied the mass savings achieved at the component structure level are
not seen in the mass of the total system. One possible reason for this is that the lighter component
structures are in premium vehicles and the mass discrepancy in the total system is a result of additional
content. This possibility was investigated and no such correlation was identified. Section 2.1.1 provides
the details on the composition of the total assembly for each example subsystem following.
2.3.1
Subsystem Examples
2.3.1.1 Front Door
Figure 2.3-1 shows the steel and aluminium door frames mass differences. Figure 2.3-2 plots the total
system mass of the same doors. Note that the doors with lighter frames are in parity with the heavier frame
doors once they have been assembled into the total door system and any mass reduction achieved is
negated at the system level. Premium vehicle classes are flagged in the parity charts and tables to illustrate
that the average masses are not inflated by this traditionally heavier vehicle class.
Figure 2.3-1: Door Frame Mass Comparison
Figure 2.3-2: Total Door System Mass Comparison
Table 2.3-1 Door Frame vs. Total System Mass Comparison Data
Frame
Mass (kg)
Total
System
Mass (kg)
%
Delta (kg)
Steel Avg
32.4
-
-
Mass Reduction
%
Delta (kg)
Mass Reduction
Steel Avg
16.3
-
-
Steel Prem
15.6
-4%
-0.7
Steel Prem
33.5
3%
1.1
Alum Avg
11.3
-30%
-5.0
Alum Avg
32.5
0%
0.1
Alum Prem
11.1
-32%
-5.2
Alum Prem
33.1
2%
0.7
For door with 1.1 m^2 area
© WorldAutoSteel 2015
For door with 1.1 m^2 area
21
2.3.1.2 Front Bumper
Figure 2.3-3 shows the differences in steel and aluminium bumper frames Figure 2.3-4 plots the total
system mass of the same bumpers. Table 2.3-2 shows that average aluminium bumper beam frames are
typically 33% (≈ 2.5kg) lower mass compared with the average steel beams. However at the system level,
the mass reduction is reduced to 21%.
Figure 2.3-3: Bumper Frame Mass Comparison
Figure 2.3-4: Total Bumper System Mass Comparison
Table 2.3-2 Front Bumper Beam vs. Total System Mass
Beam Only
Average Designs
Vehicle Subsystem
Aluminum
Steel
Front Bumper
© WorldAutoSteel 2015
6.3
Total System
Average Designs
4.2
Aluminum
Steel
%
Delta
-33%
-2.1
15.3
15.9
%
Delta
+4%
+.6
22
2.3.2
Summary of Subsystems
As shown in Table 2.3-3, most of the systems in the database do not fully benefit, or show no benefit, from
the mass savings achieved at the component level. Though identifying the cause is not a part of the scope
of this study, it is a reasonable deduction that the efforts made to reduce component mass are being lost
along the vehicle design chain.
Table 2.3-3: Mass saving potential - Steel vs. Aluminium – Structure & Total System
Vehicle Sub System
Component Mass Savings & Total System Mass Savings
Component (Structure) only
Total System
Avg.
Avg.
Avg.
Avg.
Diff
Diff
Steel
Alum
Steel
Alum
Front Doors
kg
16.3
kg
11.3
%
-30%
kg
32.4
kg
32.5
%
0%
Hood
13.5
8.1
-40%
17.2
11.4
-34%
Hatchback
11.4
8.1
-29%
21.7
20.1
-7%
Decklid
10.7
8.1
-24%
**
**
**
Liftgate
15.3
10.2
-33%
31.3
28.6
-9%
Wheel Rim
9.2
8.3
-10%
*
*
*
Front Bumper
6.3
4.2
-33%
15.3
15.9
+4%
Rear Bumper
6.2
4.3
-31%
13.7
10.8
-21%
348.3
240.7
-31%
*
*
*
Body Structure
* Structure and System are same
** Sufficient statistical data not available
© WorldAutoSteel 2015
23
2.4 There Is A Narrow Margin In Vehicle Curb Weights Between Vehicles Using
Efficient Steel Body Structures And Aluminium Body Structures
The data from Table 2.4-1 can be used to develop an approximate analysis of the total vehicle curb weight
change that can be achieved if most main subsystem mass reductions, as shown, were accomplished.
Table 2.4-1 assumes subsystem mass reductions for a typical mid-size passenger car and compares the
accumulated mass reduction to the original curb weight, which for this example is assumed to be 1500 kg.
The data show that while the state-of-the-art of the aluminum body structures in the database reduce
vehicle curb weight by 9.3% compared to average steel structures, current efficient steel structures reduce
vehicle curb weight by 6.5% compared to average steel structures, closing the gap with aluminium to just
2.8%.
Table 2.4-1: Curb Weight Reduction - Average vs. Efficient Design – Total System
Vehicle Subsystem
Average
Steel
Aluminium
Efficient Steel
kg
kg
Diff
kg
Diff
Front Doors x 4
129.6
130.0
+0.3
110.8
-18.9
Hood
17.2
11.4
-5.8
13.6
-3.6
Decklid
17.7
16.6
-1.1
16.3
-1.4
Wheel Rim x 4
Lower Control Arms x 2 (McPh)
36.8
25.5
-11.4
29.0
-7.9
16.3
11.5
-4.6
11.2
-5.0
Other Front Suspension (McPh)
34.1
27.4
-6.7
27.4
-6.7
Rear Suspension (twist beam) *
47.6
47.6
0.0
39.5
-8.1
Front Bumper
15.3
15.9
+0.6
14.8
-0.5
Rear Bumper
13.7
10.8
-2.9
10.6
-3.1
Body Structure
348.3
240.7
-107.6
305.7
-42.6
All Other Systems (no change)
823.4
823.4
0.0
823.4
0.0
Vehicle Curb Weight
Curb Wt. % Reduction:
1500
1361
-139
1402
-98
9.3%
6.5%
* Twist beam available only in steel
Note that the above 2.8% difference between steel and aluminum can be reduced even further with
continued adaptation of steel advances (see next section). For example, if an FSV-type body structure
(286.6 kg for mid-size vehicle) would be utilized in the above table, the gap could potentially be reduced to
less than 2%.
Curb Weight reduction impact on fuel consumption: The Table 2.4-1 margin of 2.8% between an
efficient steel vehicle and aluminium vehicle results in a very small change in fuel consumption (fuel
economy). Even assuming an average 30 miles per gallon (7.8 liters per 100 kilometers) vehicle with a
perfectly optimized powertrain, the largest gain that could be expected with this small mass difference is
only about 0.6 miles per gallon (0.15 liters per 100 kilometers) – a very small gain in exchange for higher
costs and poorer life cycle environmental impact.
© WorldAutoSteel 2015
24
2.5 There Is Yet Untapped Mass Savings Potential For Steel
The steel efficient designs in the current production vehicle data set provide evidence that there is, indeed,
more potential for steel to reduce structural mass. Design optimization techniques combined with AHSS
can provide cost effective mass reduction, as particularly noted when comparing aluminium average and
efficient designs to steel efficient designs.
Above and beyond what automakers themselves are demonstrating in efficient designs, WorldAutoSteel
members, both collectively and individually, have invested sizably in research and development programs
that demonstrate examples of automotive applications that can meet the challenges of mass reduction
without compromise to performance, and using manufacturing facilities and infrastructures already in place.
Following are examples:
2.5.1
FutureSteelVehicle Body Structure
Extensive use of a broad portfolio of AHSS grades, coupled with engineering design optimization, enables
a robust body structure that is feasible to produce and achieves 5-star crash performance against all global
crash standards, while also exceeding mass reduction targets. A lower weight, mass-efficient body creates
opportunities for downsizing subsystems, including the powertrain, and promotes reductions in overall
vehicle mass. As an example, the body structure mass achievement for the FSV Battery Electric Vehicle
(BEV) variant is 177 kg, including the battery tray (unique to a BEV product). This compares quite favorably
with the 2010 VW Polo, at 231 kg, which was recognized as Car of the Year in Europe as a result of its
mass-efficient design, but carries a lighter ICE gasoline powertrain. Please note Table 2.5-1 for
benchmarking comparisons.
Table 2.5-1: FSV benchmarking
Class
Powertrain
Curb Weight
Body Mass
Fuel Consumption (NEDC)
FSV – BEV
Vehicle
B+
BEV
958 kg
177 kg
2.4 l/100 km (equiv)
ULSAB - AVC
C
ICE-G
933 kg
202 kg
4.4 l/100 km
VW Polo
B
ICE-G
1067 kg
231 kg
5.7 l/100 km
2.5.2
Steel Member Company Examples5
FSV’s steel portfolio represented those grades that would be commercially available within the 2017-2025
timeframe. Steel company projects, however, demonstrate mass reduction and design efficiency using
AHSS available on the market today and achieve significant mass reduction.




An AHSS steel body structure designed within the packaging confines of an existing production vehicle
achieved 25% mass reduction with steel having average tensile strengths of 900 MPa.
An AHSS steel body structure for an electric vehicle achieved 26% mass reduction through the use of
65% (of total body weight) AHSS, which includes 45% Ultra High-Strength Steel (UHSS) grades,
combined with cost effective steel technologies.
An advanced door design that uses AHSS DP 300/500 0.55mm steel achieves 11% mass reduction,
material cost neutral.
A door design using a combination of existing AHSS and UHSS to achieve 27% mass reduction; and
another that stretches to technologies available 2017 and beyond that achieves 34% mass reduction.
These are just a few examples of steel industry efforts to help automakers achieve the necessary mass
reduction to meet new tailpipe regulations with steel that are both cost effective and implementable today.
© WorldAutoSteel 2015
25
3.0 The Cost of Lightweighting
A cost comparison study from 20016 shows that the cost of an aluminium body structure compared with a
steel structure is typically a $600 increase. This is also a rule of thumb used in the industry by some body
design engineers. A study by the National Highway Transportation Safety Administration (NHTSA)7, based
on 2011 figures, showed a cost increase of $720 for the aluminium body structure and a cost increase of
$147 for the AHSS design .
3.1
Subsystem Examples
3.1.1
Body Structure
Table 3.1-1 shows the body structure material type and mass reduction potential based on the benchmark
data from this study. Comparing the aluminium structure to the FSV AHSS shows a mass saving of 45.9
kg (286.6kg - 240.7kg). This mass saving will be achieved at an additional cost of $573 ($720 - $147),
equivalent to $12.49 per kg saved, a relatively high premium to pay for mass reduction.
Table 3.1-1: Body Structure Material Comparison
Body Material Options
Steel Average
Steel - Alum
Steel Efficient
FSV - AHSS
Aluminium Efficient
3.1.2
Body & Engine Cradle
Mass (kg)
348.3
329.9
305.7
286.6
240.7
Compared to FSV
Plan View Area: 8.75 m^2
GVW: 1928 kg (Mid Size Sedan)
Mass Reduction
%
Delta (kg)
-5%
-12%
-18%
-31%
-16%
18.4
42.5
61.7
107.5
45.9
Door Structure
The EDAG NHTSA study showed a cost increase of $24.80 for the aluminium door structure and a cost
increase of $5.12 for the AHSS design. Table 3.1-2 shows the door structure material type and mass
reduction potential based on the benchmark data from this study. Comparing the aluminium structure to the
AHSS shows an additional mass saving of 2.82 kg (12.92kg – 10.10kg). This mass saving will be achieved
at an additional cost of $19.68 ($24.80 - $5.12), equivalent to $6.98 per kg saved.
Table 3.1-2: Front Door Frame Material Comparison
Door
Material Option
Steel Average
Alum Average
Steel Efficient
Alum Efficient
3.1.3
Mass Reduction
Frame Mass
%
Delta (kg)
(kg)
16.3
11.3
-30%
5.0
12.9
10.1
-22%
2.8
For door with 1.1 m^2 area
Hood Structure
According to the NHTSA study, a cost increase of $21.26 could be expected for the aluminium hood
structure and a cost increase of $4.74 for the AHSS design. Table 3.1-3 show the hood structure material
© WorldAutoSteel 2015
26
type and mass reduction potential based on the benchmark data from this study. Comparing the aluminium
structure to the steel efficient (AHSS) shows an additional mass saving of 3.52 kg (10.42kg – 6.90kg). This
mass saving will be achieved at an additional cost of $16.52 ($21.26 - $4.74), equivalent to $4.69 per kg
saved.
Table 3.1-3: Hood Frame Material Comparison
Hood Material
Option
Frame Mass
(kg)
Steel Average
13.5
Alum Average
8.1
Steel Efficient
10.4
Alum Efficient
6.9
Mass Reduction
%
Delta (kg)
-40%
5.4
-34%
3.5
For Hood with 1.68 m² area
3.2
Relationship Between Cost and Fuel Efficiency
The NHTSA study sought to identify the maximum feasible weight reduction possible using lightweighting
technologies which will be available in the years 2017 to 2025, to achieve fuel reduction savings standards
as set by the Administration, while keeping costs to within 10%, plus or minus, over the baseline vehicle.
Constraints of the study required the same vehicle footprint, styling and utility as the baseline vehicle (2011
Honda Accord) in passenger space, options, and luggage and towing capability.
The study investigated four alternative lightweighting structural material concepts: 1) An AHSS-intensive
design, which reduced mass by 19% compared to the baseline vehicle; 2) A Light Weight Vehicle Design
which combined an AHSS body structure with aluminium closures, reduced mass by 22%; 3) an aluminiumintensive design, which reduced mass by 25%; and 4) a multi-material design (aluminum, magnesium and
carbon fiber reinforced plastics) that reduced mass by 28%.
Relative to the 2011 baseline, all scenarios reduce curb weight mass from 20% to 30% and increase fuel
economy from the baseline 27 mpg to approximately 32 mpg (Figure 3.2-1). The study does not include
enhanced powertrain efficiencies nor does it account for the reduced mass savings at the systems level
shown by some aluminum designs, which would reduce both the curb mass savings and the fuel economy
gains.
A further comparison between the alternative advanced material solutions in Figure 3.2-1 shows that the
alternatives to AHSS save the consumer about one fuel fill-up per year. This fuel saving cannot offset the
increase in manufacturing costs associated with these materials over the average six-year ownership of a
vehicle, per a recent R. L. Polk8 study.
© WorldAutoSteel 2015
27
Concept Design
AHSS Intensive
Material
Applications
AHSS Body
AHSS Closures
AHSS Chassis
LWV
AHSS Body
Alum Closures
Alum Chassis
Alum Intensive
Alum/Mag/CFRP
Alum Body
Alum Closures
Alum Chassis
CFRP Body
Alum/Mag Closures
Alum Chassis
Structural Material Content
Conventional Steel
AHSS
Aluminum
Magnesium
Carbon Fiber
Curb Weight (kg)
1197 kg
1149 kg
1108 kg
1060 kg
-
4%
7%
11%
$210
$820
$2,680
31.4
31.6
31.8
32.0
1.1
1.5
Years to Recover Manufacturing
Cost in Fuel Saving(@$4.00/gal)
-
0.4
8.6
11.5
28.6
Increased LCA CO2 (Tonnes)
-
0.4
1.0
4.4
% Curb Weight Reduction
Manufacturing Cost Premium
Fuel Economy (mpg)
Reduced Fuel Fill-up/year
Figure 3.2-1: NHTSA Vehicle Results
Source: NHTSA Report7
3.3
Summary
Based on previous analysis conducted by EDAG, it was determined that the cost of lightweighting for the
three subsystems reviewed could amount to more than US$12.00/kg of mass reduction. A recent Ricardo
study9 based on a survey of European OEMs indicated that there is an EU€5.00/kg limit to what OEMs are
currently willing to pay for mass reduction. Further, the NHTSA study indicated that the cost of
lightweighting with aluminium or a multi-material design would be US$820 and US$2,680 per vehicle (body
structure + closures + chassis), respectively, and would require as many as 28 years to recover
manufacturing costs in fuel savings. At current prices, use of aluminium for lightweighting is cost prohibitive
for some applications.
This report shows that benchmarking is an important tool in analyzing the value of competitive material
lightweighting, considering their effectiveness to achieve actual mass reduction at the subsystem level, and
when compared to steel efficient designs.
© WorldAutoSteel 2015
28
4.0 Life Cycle Assessment
Auto Mass Benchmarking study, to investigate the life cycle greenhouse gas (GHG) impact of three
principal material usage categories in the body structure subsystems represented in the A2Mac1 data:
1. Average steel design – Using regression methodology, EDAG developed a power model to
determine an estimated mass of each subsystem based on the influence of a primary mass driver.
In the case of the body structure, the primary mass driver is gross vehicle weight (GVW).
2. Efficient steel design – The model developed for the average steel designs was iteratively
manipulated until it was representative of the 17 most efficient steel designs.
3. Efficient aluminium design – A power model of the most efficient aluminium designs was developed
in the same way as for the efficient steel designs.
These three categories were further compared with a fourth category, developed from body structure
designs taken from the FSV program. FSV is a clean-sheet vehicle architecture that offers mass-efficient,
steel-intensive solutions to automotive lightweighting challenges.
The estimation of life cycle GHG emissions was conducted using the UCSB Automotive Materials GHG
Comparison Model4. The UCSB Model was designed to quantify the energy and GHG impacts of
automotive material substitution on a total vehicle life cycle basis, under a broad range of conditions and in
a completely transparent fashion, and has been peer-reviewed.
4.1
Model Parameters
4.1.1
Body structure mass
Body structure masses from each of the four categories were applied to two vehicle classes as defined by
the NHTSA7 study:


Passenger Car/Light (PC/L) – curb weight 907-1134 kg
Passenger Car/Compact (PC/C) – curb weight 1134-1360 kg
Mass drivers for vehicles in the A2Mac1 data that fit these categories were averaged and used in the
appropriate models to generate an estimated average body structure mass for each category and class.
The FSV design masses were averaged into the two NHTSA classes as follows:


FSV1 (2 A-B class designs) – PC/L
FSV2 (2 C-D class designs) – PC/C
Table 4.1-1 provides the resulting body structure average masses:
Table 4.1-1: Average Mass of Body Structures in kg
NHTSA
Class
© WorldAutoSteel 2015
# in
A2Mac1
GVW (kg)
Average
Steel
Efficient
Steel
Efficient
Aluminum
FSV
PC/L
11
1487
250.1
219.5
172.9
195.9
PC/C
16
1714
295.1
259.0
204.0
216.7
29
4.1.2
Bill of Materials (BOM) Calculations
The bill of materials (BOM) for each design was calculated using the average curb mass of each category
and class (Table 4.1-2). The UCSB model contains default values for each material as a percentage of
curb mass. These defaults include a distribution in the body structure of 90% flat/10% long for steel designs,
and 70%flat/30% extruded for aluminium designs.
Table 4.1-2: Bill of Materials in kg
Passenger Car/Light (PC/L)
Flat carbon steel
Long steel
Cast iron
Flat AHSS
Long AHSS
Rolled aluminum
Extruded aluminum
Cast aluminum
Other
Plastic
Rubber
Glass
Copper
Other
Fluids
Tires
Vehicle mass
Average
Steel
Efficient
Steel
Efficient
Alum
373
140
93
0
0
9
9
47
350
112
28
28
19
75
29
60
1022
148
115
93
198
22
9
9
47
350
112
28
28
19
75
29
60
992
148
115
93
0
0
130
61
47
350
112
28
28
19
75
29
60
945
Passenger Car/Compact (PC/C)
FSV1
148
115
93
176
20
9
9
47
350
112
28
28
19
75
29
60
968
Average
Steel
Efficient
Steel
Efficient
Alum
464
174
116
0
0
12
12
58
414
139
35
35
23
93
29
60
1249
198
144
116
233
26
12
12
58
414
139
35
35
23
93
29
60
1213
198
144
116
0
0
154
73
58
414
139
35
35
23
93
29
60
1158
FSV2
198
144
116
195
22
12
12
58
414
139
35
35
23
93
29
60
1170
Other key parameters include:
 Recycling methodology – in accordance with the Declaration by the Metals Industry on Recycling
Principles10, the avoided burden method, in which credit is given for producing material (scrap) that
allows a downstream user to avoid production of primary material, was used.
 Power train - for purposes of determining the use phase impacts, a conventional gasoline
powertrain has been assumed.
 Lifetime Driving Distance (LTDD) –A2Mac1 database includes cars from all OEMs, and because
automotive GHG modeling is very sensitive to this parameter, results were calculated using both
European (150,000 km) and North American (250,000 km) averages for LTDD.
 Powertrain resizing – because the model is also very sensitive to the decision whether or not to
resize the powertrain to take full advantage of mass reduction, results have been calculated both
with and without resizing.
 Secondary mass change – as the mass differences involved in this study are relatively small (in
all cases <100 kg), no secondary mass effects have been considered.
 Driving cycle – the New European Driving Cycle (NEDC) was used.
 Fuel Consumption – the UCSB model relies on baseline fuel consumption and weight elasticity
values (WEV) developed by Forschungsgesellschaft Kraftfahrwesen mbH Aachen (fka)11. For
purposes of this case study, the baseline fuel consumption and WEV for the compact class (NEDC
driving cycle) was used. This WEV equates to a fuel reduction value (FRV) of .102 l/100kg/100km
© WorldAutoSteel 2015
30
when the powertrain is not resized, and .282 l/100kg/100km when the powertrain is resized. The
compact class baseline fuel consumption given by fka is 5.56 l/100km.
4.2
Body Structure Results
4.2.1
Total Life Cycle GHG Emissions
The results (Table 4.2-1) show that, for all eight scenarios studied, the efficient steel design yields the lowest
life cycle GHG emissions, with GHG savings over the baseline average steel designs of 193 to 798 kg CO2e.
The FSV designs show the potential for an additional 118 to 721 kg GHG reduction. The possibility for
unintended consequences is apparent from the results of the aluminium designs. In all cases, except the
two that combine the 250,000 km driving distance with optimum powertrain resizing, the aluminium design,
while producing the lowest use phase emissions, shows a net increase in GHG emissions over the existing
average steel design. Even in the two scenarios for which the aluminium design shows life cycle GHG
emissions lower than the baseline, it is clear that in order to minimize emissions, an efficient steel design is
the right choice.
Table 4.2-1: Relative GHG Emissions in kgCO2e – Body Structure
Passenger Car/Light (PC/L)
Average
Steel
(baseline)
Passenger Car/Compact (PC/C)
Efficient
Steel
Efficient
Alum
FSV1
Average
Steel
(baseline)
Efficient
Steel
Efficient
Alum
FSV2
No
Resizing
150000
-
-190
623
-337
-
-224
736
-488
250000
-
-277
403
-492
-
-327
476
-711
With
Resizing
150000
-
-420
42
-745
-
-496
50
-1,078
250000
-
-661
-565
-1,172
-
-779
-667
-1,695
The results (Table 4.2-1) show that, for all eight scenarios studied, the efficient steel design yields the lowest
life cycle GHG emissions, with GHG savings over the baseline average steel designs of 193 to 798 kg CO2e.
The FSV designs show the potential for an additional 118 to 721 kg GHG reduction. The possibility for
unintended consequences is apparent from the results of the aluminium designs. In all cases, except the
two that combine the 250,000 km driving distance with optimum powertrain resizing, the aluminium design,
while producing the lowest use phase emissions, shows a net increase in GHG emissions over the existing
average steel design. Even in the two scenarios for which the aluminium design shows life cycle GHG
emissions lower than the baseline, it is clear that in order to minimize emissions, an efficient steel design is
the right choice.
4.2.2
Body Structure GHG Emissions by Life Cycle Phase
GHG emissions for each combination of class and driving distance are displayed by life cycle phase in
Figures 4.2-1 through 4.2-4. For all eight cases studied, the efficient steel and FSV designs show a
consistent pattern:



Lower production phase emissions due to the reduced amount of material required.
Lower use phase emissions due to reduced mass of the vehicle.
Slightly higher EOL emissions due to smaller credit for recycling because less material goes into
the vehicle, less EOL scrap is available for downstream recycling.
The effect of this pattern is, as outlined above, lower total emissions. The slightly higher EOL impact is
outweighed by savings in the production and use phases. The two aluminium designs show a different, but
still consistent, pattern:
© WorldAutoSteel 2015
31



Significantly higher production phase emissions due to energy-intensive aluminium production.
Lower use phase emissions due to reduced mass of the vehicle.
Significantly lower EOL emissions due to larger credit for recycling – recycling credit is based on
the difference between primary and secondary material production, and for aluminium this
difference is relatively high.
The effect of this pattern is higher overall emissions, except for the two cases that assume both the 250,000
km LTDD and optimal resizing of the powertrain (Figures 4.2-1 and 4.2-2). The lower use and EOL phase
emissions are outweighed by the increase in the production phase.
Without Powertrain Resizing
Average
Steel
(baseline)
Efficient
Steel
Efficient
Aluminium
Production
0
-101
Use
0
-131
End of Life
0
Total
0
With Powertrain Resizing
FSV1
Average
Steel
(baseline)
Efficient
Steel
Efficient
Aluminium
FSV1
2519
-180
0
-101
2519
-180
-330
-232
0
-361
-911
-640
42
-1566
74
0
42
-1566
74
-190
623
-337
0
-420
42
-745
Figure 4.2-1: Relative GHG Emissions by driving distance- PC/L, 150,000 km
© WorldAutoSteel 2015
32
Without Powertrain Resizing
Average
Steel
(baseline)
Efficient
Steel
Efficient
Aluminium
0
-101
Use
0
End of Life
0
Production
With Powertrain Resizing
FSV1
Average
Steel
(baseline)
Efficient
Steel
Efficient
Aluminium
FSV1
2519
-180
0
-101
2519
-180
-218
-550
-386
0
-601
-1519
-1066
42
-1566
74
0
42
-1566
74
0
-277
403
-492
0
-661
-565
Figure 4.2-2: Relative GHG Emissions by driving distance - PC/L, 250,000 km
Total
Without Powertrain Resizing
Average
Steel
(baseline)
Efficient
Steel
Efficient
Aluminium
Production
0
-120
Use
0
-154
End of Life
0
49
Total
© WorldAutoSteel 2015
-1172
With Powertrain Resizing
FSV1
Average
Steel
(baseline)
Efficient
Steel
2973
-260
0
-390
-335
0
-1848
107
0
Efficient
Aluminium
FSV1
-120
2973
-260
-425
-1075
-925
49
-1848
107
0
-224
736
-488
0
-496
50
Figure 4.2-3: Relative GHG Emissions by driving distance- PC/C, 150,000 km
-1078
33
Without Powertrain Resizing
Average
Steel
(baseline)
Efficient
Steel
Efficient
Aluminium
0
-120
Use
0
End of Life
0
Total
0
Production
With Powertrain Resizing
FSV1
Average
Steel
(baseline)
Efficient
Steel
Efficient
Aluminium
FSV1
2973
-260
0
-120
2973
-260
-257
-649
-559
0
-709
-1792
-1542
49
-1848
107
0
49
-1848
107
-327
476
-711
0
-779
-667
-1695
Figure 4.2-4: Relative GHG Emissions by driving distance - PC/C, 250,000 km
4.3
Other Systems
Six additional subsystems described in the A2Mac1 database were analyzed in the same manner: Front
Bumper, Rear Bumper, Wheels (4 wheels), Hatchback, Hood, and Front Door (2 doors). Because of the
relatively small mass of these subsystems, no powertrain resizing was considered.
Only the three categories (average steel, efficient steel, efficient aluminum) from the A2Mac1 database
were considered, since the comparison efficient steel vehicle, FSV, did not include designs for the other
subsystems.
4.3.1
Subsystem Masses
Table 4.3-1 : Subsystem Masses (kg)
Passenger Car/Light (PC/L)
Front Bumper
Rear Bumper
Wheels
Hatchback
Hood
Front Door
© WorldAutoSteel 2015
Average
Steel
(baseline)
Efficient Steel
4.5
4.4
35.1
11.4
8.8
30.9
2.4
1.9
27.5
8.7
6.8
24.6
Passenger Car/Compact (PC/C)
Efficient
Aluminum
Average
Steel
(baseline)
Efficient Steel
Efficient
Aluminum
2.1
1.5
24.2
7.6
4.5
19.2
5.4
5.3
41.7
12.2
11.3
32.6
2.9
2.3
32.7
9.2
8.8
25.9
2.5
1.8
28.8
8.1
5.8
20.3
34
4.3.2
LCA Results
The LCA results in Table 4.3-2 show a trend similar to that of the body structure analysis. In 14 of the 24
scenarios studied, the efficient aluminum design shows the unintended consequence of higher life cycle
emissions than the baseline design. And, in all scenarios, the efficient aluminium design shows higher life
cycle emissions than the efficient steel design. As in the case of the body structure, the most efficient steel
design shows the lowest life cycle emissions in all cases.
Table 4.3-2 : Relative Difference in Total Life Cycle GHG Emissions in kg CO2e - Subsystems
Passenger Car/Light (PC/L)
Front Bumper
Rear Bumper
Wheels
Hatchback
Hood
Front Door
© WorldAutoSteel 2015
Avg Steel
(baseline)
150000
Passenger Car/Compact (PC/C)
Efficient Steel
Efficient
Aluminum
Avg Steel
(baseline)
Efficient Steel
Efficient
Aluminum
0
-13
0
0
-16
0
250000
0
-19
-7
0
-23
-8
150000
0
-16
-8
0
-19
-9
250000
0
-23
-16
0
-27
-19
150000
0
-48
101
0
-57
121
250000
0
-69
71
0
-82
84
150000
0
-17
29
0
-19
31
250000
0
-25
18
0
-27
19
150000
0
-13
4
0
-16
6
250000
0
-18
-8
0
-24
-10
150000
0
-40
61
0
-42
64
250000
0
-58
27
0
-61
29
35
5.0 Conclusions
The challenges of reduced tailpipe emission standards are driving the industry to find ways to reduce
vehicle mass. A study commissioned by WorldAutoSteel and the Steel Market Development Institute
(SMDI) sought to analyze mass and material data for a variety of automotive components/subsystems from
a database constructed and owned by A2Mac1, a global automotive benchmarking company, to understand
the current state of lightweighting in production vehicles and identify further opportunities. This study helps
identify gaps in the process of lightweighting vehicles by evaluating current production vehicles.
Moreover, this study demonstrates the power of statistical benchmarking and the limitations of a one-off
tear down of an efficient vehicle. Statistical benchmarking gives an entirely new perspective, a positive
breakthrough in vehicle mass comparison and target setting. Using this methodology, an automotive
designer can look at subsystems from a large body of vehicle data and identify those that are much lighter
than the ‘average’ vehicle. It provides a means to set subsystem targets on a more accurate basis than that
which is being accomplished in the industry today. It creates a better road to holistic design and real
progress in mass efficiency.
The study revealed five key findings.
1. Today’s steel designs vary drastically in efficiency.
2. When compared to an efficient steel design, the mass savings gap with aluminium significantly
reduces.
3. Mass savings achieved at the component level are often not realized at the system level.
4. There is a narrow margin in curb weights between vehicles using efficient steel body structures and
aluminium body structures.
5. Based on these four previous findings, it can be understood that there is yet untapped mass savings
potential for steel.
The data shown in this report for current production vehicles illustrates that there is disconnect between the
level of lightweighting efforts in the automotive industry and the results actually achieved. It also shows
that there is a great deal more opportunity to achieve this lightweighting with design optimization, advanced
steels and steel technologies.
Considering the vehicle curb weight savings gap of just 2.8% between aluminium and efficient steel
designs, the cost incurred with aluminium materials is not justifiable.
Most importantly, from a total life cycle perspective, the mass savings achieved by aluminium in current
production vehicles is not resulting in a smaller vehicle emissions footprint overall. For all cases studied,
the efficient steel designs show a consistent pattern of lower emissions in production, use and EOL, which
results in lower total cycle emissions. The aluminium designs showed higher production phase emissions
due to the energy-intensive manufacturing process, which is offset neither by the reduced use phase
emissions nor the significantly lower EOL due to the larger recycling credit.
It is important to consider the impact of any light weighting technology on the total mass of the system
assembly. Each light weighting technology requires unique methods of assembly and localized mounting
requirements for other components. Additional mass may need to be added to accommodate such
© WorldAutoSteel 2015
36
requirements. Often additional consumer features are added to the product, offsetting the structure mass
saving.
Regulations based on tailpipe emissions drive the use of low density materials, such as aluminium, to
achieve fleet average fuel consumption targets. However, as these challenges are faced during the vehicle
design process, the value of the lightweighting technology must be properly weighed against cost and life
cycle emissions.
5.1
Final Observations on the Power of Statistical Benchmarking as a Tool for
Mass Efficiency
As demonstrated by these study results, the following observations can be applied to the next generation
of automotive design to ensure that future vehicles are safe, environmentally efficient, and remain
affordable to manufacture:

Statistical mass benchmarking is critical, as demonstrated in this study, to ensure that subsystem mass
targets are accurately set. WorldAutoSteel has made available, through its member companies, an
Auto Mass Benchmarking Calculator that uses the same regression models and data employed in this
study to enable quick comparisons of new or existing designs to the A2Mac1 vehicle database study
results. Contact your member company representative for more information.

Statistical mass benchmarking is also important to ensure that the value of the lightweighting option in
terms of mass reduction validates the extra cost involved in using alternative materials. The question
should be raised: Could a more efficient, holistic design provide the same or better mass reduction
advantages, at less cost than an alternative material?

It is crucial that mass reduction goals achieved at one place along the design chain are supported
throughout the system design to ensure that the savings are maintained and optimized in the final
subsystem.

A Life Cycle Assessment should be conducted to ensure that compromises made to achieve lower
tailpipe emissions do not result in a net increase in total life cycle emissions. Continuing on the track
of focusing only on tailpipe emissions will result in an automotive sector whose efforts and expense to
reduce vehicle environmental footprint may result in the unintended consequence of a net increase for
future generations to address.
WorldAutoSteel members can make the full data results of this Auto Mass Benchmarking project available
to customers, and cooperate with them to address mass efficiency in vehicle designs. As this project
proceeds to further data updates and analysis in future phases, we will continue to make data and findings
freely available at worldautosteel.org.
© WorldAutoSteel 2015
37
Annotations
1
Malen, Donald E., Hughes, Jason, Mass Benchmarking Using Statistical Methods Applied to Automotive
Closures, Paper No. 2015-01-0574, (April 2015)
2
FutureSteelVehicle (May 2011, May 2013), available at www.worldautosteel.org
3
Davies, Jim; Singh, Harry, Automotive Front Door Benchmarking (Light Weight Door Structure), (2013)
unpublished.
4
Geyer, Roland: The Example of Mild Steel, Advanced High Strength Steel and Aluminium in Body in
White Applications Methodology Report (December 2007). The Methodology Report and a free download
of the UCSB Automotive Greenhouse Gas Materials Comparison Model are available at
http://www.worldautosteel.org/projects/vehicle-lca-study/assessments-of-automotive-material/
5
Steel Study Examples cited:
a. U. S. Steel Body-In-White (2013)
b. Kim, Jaehyun; Lee, Hongwoo; Chung, Kyunghwan; Lee, Hyounyoung; Kang, Yeonsik; Nam,
Jaebok, POSCO, Republic of Korea, A New Body Concept For Electric Vehicle: PBC-EV, FISITA
Paper No. F2012-E04-020 (November, 2012)
c. Hoffman, Oliver G, InCar The Innovative Solution Kit for the Automotive Industry (October 2009)
d. ArcelorMittal, ArcelorMittal unveils new ultra lightweight car door solutions offering up to 34 percent
weight savings over existing steel car doors (news release 25 June 2013)
6
Kelkar et al, Automobile Bodies: Can Aluminium Be an Economical Alternative to Steel? (August 2001
Issue of JOM., 53 (8) (2001) pp. 28-32).
7
Singh, Harry, Mass Reduction for Light-Duty Vehicle Models Years 2017 – 2025 Final Report, NHTSA
Report DOT HS 811666 (http://www.nhtsa.gov), U. S. Steel Summary Analysis (August 2012,).
8
Polk, R.L. & Company, “Length of U.S. Vehicle Ownership Hits Record High”, (Feb 2012),
https://www.polk.com/knowledge/polk_views/length_of_u.s._vehicle_ownership_hits_record_high
9
Ricardo AEA, Improving the understanding of the potential for weight reduction in cars and vans (May
2014)
10
AISI, et al., Declaration by the Metals Industry on Recycling Principles, International Journal of Life
Cycle Assessment, 2006
11
fka, Wohlecker, Roland, et al., Determination of Weight Elasticity of Fuel Economy for Conventional
ICE Vehicles, Hybrid Vehicles and Fuel Cell Vehicles, fka, Report 55510, June 2007.
© WorldAutoSteel 2015
38
Appendix 1 – Model Equations
The table of results below (Table A1-1) summarizes the mass drivers for each of the subsystems and shows
the ‘power model’ predictive equations for the ‘average’ and the ‘mass efficient’ designs. The
accuracy/quality of the predicted mass by these equations is indicated by the R² value calculated by the
‘regression’ analysis. An R² value of 0.6 indicates that 60% variation in the data point values is accounted
for by the chosen variables/attributes in the equation. For R² values less than 0.5 the mass efficient options
identified should be further reviewed and engineering judgment should be applied to identify the designs
for further study. Comparison of the R² values for all the systems is shown in Table A1-2. When interpreting
the results one should also understand that the A2Mac1 data base could have measurement and recording
errors as the vehicle teardown process involve manual part disassembly, weighing and recording of mass
and material type data. Some of the data for material type was corrected in this study, especially for the
doors, where a previous SMDI study had identified some discrepancies.
Table A1-1: Model Summary of Subsystem Mass Drivers
A. Front Door
Linear model: door frame mass estimate
4.205
5.10
0.00
13.57
1.06
0.47
0.00
Power model: frame mass estimate
.
2
R = 0.56,
.
.
.
²
.
.
.
Standard Error = 1.123
Power model: Mass estimate for steel efficient design
² .
.
.
.
.
.
.
.
Power model: Mass estimate for aluminum efficient design
² .
.
.
.
.
.
N Values: Steel – 1.12
B. Hood
.
.
Aluminium – 1.0
Linear model: hood frame mass estimate
7.11
8.75
6.09
0.00
Power model: frame mass estimate
.
R2 = 0.80,
.
.
.
Standard Error = 1.177
Power model: Mass estimate for steel efficient design
© WorldAutoSteel 2015
39
.
.
.
.
.
Power model: Mass estimate for aluminum efficient design
.
.
.
N Values: Steel – 1.2
C. Hatchback
.
.
Aluminium – 1.0
Linear model: hatchback frame mass estimate
0.35
4.67
,
0.0042
3.36
0.00
,
Power model: frame mass estimate
.
.
²
R2 = 0.50,
.
.
.
,
Standard Error = 1.138
Power model: mass estimate for steel efficient design
² .
.
.
,
.
.
.
Power model: mass estimate for aluminum efficient design
² .
.
.
.
N Values: Steel – 1.1
D. Decklid
.
,
.
Aluminium – .09
Linear model: decklid frame mass estimate
2.22
4.429
2.71
0.00
,
1.32
0.00
1.07
0.00
Power model: frame mass estimate
.
R2 = 0.50,
.
.
.
.
.
²
.
.
Standard Error = 1.15
Power Model: Mass estimate for steel efficient design
.
² .
.
.
.
.
.
.
.
Power Model: Mass estimate for aluminum efficient design
.
² .
.
N Values: Steel – 1.05
© WorldAutoSteel 2015
.
.
.
.
.
.
Aluminium – .09
40
E. Liftgate
Linear model: liftgate frame mass estimate
9.08
3.02
,
.
Power model: frame mass estimate
.
R2 = 0.15,
²
.
Standard Error = 1.194
Power model: mass estimate for steel efficient design
² .
.
.
.
Power model: mass estimate for aluminum efficient design
² .
.
.
.
N Values: Steel – 1.05
F. Instrument Panel Beam
Aluminium – 1.25
Linear model: IP Beam mass estimate
6.45
0.0
3.376
0.0079
Power Model: Beam mass estimate
R2 = 0.36,
G. Front Bumper Beam
.
.
.
.
Standard Error = 1.310
Linear model: bumper beam mass estimate
9.07
0.0040
,
0.00743
0.86
0.00
1.27
0.00
2.59
0.00
,
Power Model: Bumper beam mass estimate
.
.
.
.
.
.
.
R2 = 0.48,
.
.
Standard Error = 1.346
Power Model: Mass estimate for steel efficient design
.
.
,
.
.
.
.
.
.
.
.
Power Model: Mass estimate for aluminum efficient design
.
.
.
.
N Values: Steel – 1.40
© WorldAutoSteel 2015
.
,
.
.
.
.
Aluminium – 1.05
41
H. Rear Bumper Beam
Linear model: bumper beam mass estimate
1.19
0.00
2.00
0.00
Power Model: Bumper beam mass estimate
3.07
0.0046
,
R2 = 0.44,
.
.
.
.
.
Standard Error = 1.439
.
Power Model: Mass estimate for steel efficient design
.
.
.
.
.
.
.
Power Model: Mass estimate for aluminum-plastic efficient design
.
.
.
I. Wheel Rim
.
.
.
.
N Values: Steel – 1.60 Aluminium/plastic – 1.40
Linear model: wheel rim mass estimate
12.20
0.0369
,
0.0276
,
1.31
0.00
Power model: wheel mass estimate
.
.
,
R2 = 0.56,
.
.
.
Standard Error = 1.158
Power Model: Mass estimate for steel efficient design
.
.
,
.
.
.
.
Power Model: Mass estimate for aluminum efficient design
.
.
,
.
N Values: Steel – 1.1
© WorldAutoSteel 2015
.
.
.
Aluminium – 1.12
42
J. Body Structure
Linear model: body structure mass estimate
154.5
0.098
,
21.37
0.00
110.9
126.7
²
Body structure and engine cradle mass estimate
.
.
R2 = 0.87,
²
.
Standard Error = 1.085
.
.
.
Mass estimate for steel efficient design
.
.
² .
.
.
.
Mass estimate for aluminum efficient design
.
.
² .
.
.
.
Mass estimate for FSV - AHSS design
.
.
² .
.
N Values: Steel – 1.05
.
.
Aluminium – 0.875
FSV-AHSS – 1.12
Table A1-2: Comparison of R² Values
Vehicle Subsystem
EDAG 2013
0.56
Malen 2010
Hood
0.80
0.77
Hatchback
0.50
0.31
Decklid
0.50
0.72
Liftgate
0.15
0.41
Wheel Rim
0.56
0.38
Rear Bumper
0.48
0.31
Front Bumper
0.44
0.49
Body Structure
0.87
0.83
IP
0.36
0.24
Front Door
© WorldAutoSteel 2015
Power Model R²
0.45
43
WorldAutoSteel
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Belgium
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The Netherlands
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© WorldAutoSteel 2015
World Steel Association
worldsteel.org