Life Cycle Assessment of Vehicle Lightweighting: Novel Mathematical

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Life Cycle Assessment of Vehicle Lightweighting: Novel Mathematical Methods to Estimate Use-Phase Fuel Consumption Hyung Chul Kim,*,† Timothy J. Wallington,† John L. Sullivan,‡ and Gregory A. Keoleian§ †

Systems Analytics and Environmental Sciences Department, Ford Motor Company, Dearborn, Michigan 48121-2053, United States Board Member, Center for Sustainable Systems, School of Natural Resources and Environment, University of Michigan, Dana Building, 440 Church Street, Ann Arbor, Michigan 48109-1041, United States § Center for Sustainable Systems, School of Natural Resources and Environment, University of Michigan, Dana Building, 440 Church Street, Ann Arbor, Michigan 48109-1041, United States ‡

S Supporting Information *

ABSTRACT: Lightweighting is a key strategy to improve vehicle fuel economy. Assessing the life-cycle benefits of lightweighting requires a quantitative description of the use-phase fuel consumption reduction associated with mass reduction. We present novel methods of estimating mass-induced fuel consumption (MIF) and fuel reduction values (FRVs) from fuel economy and dynamometer test data in the U.S. Environmental Protection Agency (EPA) database. In the past, FRVs have been measured using experimental testing. We demonstrate that FRVs can be mathematically derived from coast down coefficients in the EPA vehicle test database avoiding additional testing. MIF and FRVs calculated for 83 different 2013 MY vehicles are in the ranges 0.22−0.43 and 0.15−0.26 L/(100 km 100 kg), respectively, and increase to 0.27−0.53 L/(100 km 100 kg) with powertrain resizing to retain equivalent vehicle performance. We show how use-phase fuel consumption can be estimated using MIF and FRVs in life cycle assessments (LCAs) of vehicle lightweighting from total vehicle and vehicle component perspectives with, and without, powertrain resizing. The mass-induced fuel consumption model is illustrated by estimating lifecycle greenhouse gas (GHG) emission benefits from lightweighting a grille opening reinforcement component using magnesium or carbon fiber composite for 83 different vehicle models. Environmental Protection Agency (EPA) database. 5 We estimated MIF of 0.2−0.5 L/(100 km 100 kg) for 2013 Model Year ICEVs based on the U.S. Federal Test Procedure (FTP) combined (55-city/45-highway) cycle.4 The present work builds on our previous study and shows how both MIF and fuel reduction values (FRVs) can be calculated for specific vehicle models using information available in the EPA vehicle test database. We illustrate how these model-specific MIF and FRVs can be used to determine the use phase fuel consumption in LCAs of vehicle lightweighting. Use of model-specific MIF and FRVs in future LCAs will reduce the uncertainty regarding the benefits of lightweighting. MIF and FRV are two different LCA metrics which can be used to estimate the fuel consumption benefits of vehicle lightweighting. The former allocates a portion of total vehicle fuel consumption normalized by vehicle mass to mass-related energy use over total energy use.4 Unlike MIF, FRVs are physically observable and measurable and are defined as the rates of change of vehicle fuel consumption with changes in mass.6 In the past, FRVs have been measured using simulation7,8 or vehicle

1. INTRODUCTION Lightweighting by material substitution is a key strategy to reduce fuel consumption and greenhouse gas emissions during vehicle operation. Life cycle based analyses are required to assess the net benefits of lightweighting since production of lightweight materials (e.g., aluminum, magnesium, and carbon composites) is generally more energy intensive than for conventional materials such as steel and steel alloys.1−3 The conclusions from life cycle assessments (LCAs) of the benefits of vehicle lightweighting are often inconsistent due to incongruous modeling methods and parameters employed. LCA practitioners face a challenge of estimating the fuel consumption during the operation of lightweighted vehicles; the most energy consuming stage of the vehicle life cycle.2,4 Fuel reduction values (FRVs) needed to calculate fuel savings from lightweighting are not typically available for specific vehicle models. Previous LCA studies have used generic estimates of FRVs in the ranges 0.2−0.3 and 0.3−0.5 L/100 km per 100 kg without and with powertrain adjustment, respectively.4 The range of FRV values employed leads to different LCA results and to uncertainty regarding the benefits of lightweighting. In our previous study,4 we proposed a method of estimating the Mass-Induced Fuel Consumption (MIF) for specific models of internal combustion engine vehicles (ICEVs) based on their fuel economy and dynamometer test data available in the U.S. © 2015 American Chemical Society

Received: Revised: Accepted: Published: 10209

April 1, 2015 July 4, 2015 July 13, 2015 July 13, 2015 DOI: 10.1021/acs.est.5b01655 Environ. Sci. Technol. 2015, 49, 10209−10216

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Environmental Science & Technology Table 1. Parameters Used to Estimate Fw and Fx parameter/ constant A B C Hf ηt ηi α ∫ av dt ∫ v dt ∫ v3dt ∫ v2 dt ∫ dt

definition

unit

value

reference

target coefficientrolling target coefficientrotating target coefficientaerodynamic lower heating value of fuel transmission efficiency including losses in final drive indicated (thermodynamic) engine efficiency power demand from accessories

N N/(m/s) N/(m/s)2 J/L

taken from EPA fuel economy test database taken from EPA fuel economy test database taken from EPA fuel economy test database 32.3 × 106 (gasoline) 0.88 (automatic); 0.95 (manual) 0.41 (gasoline) 750 city = 3090; highway = 1165; combined = 2224 city = 17 769; highway = 16 507; combined = 17 201 city = 4 549 907; highway = 8 540 124; combined = 6 345 505 city = 263 621; highway = 371 739; combined = 312 274 city = 1874; highway = 765; combined = 1375

5 5 5

W m2/s2 m m3/s2 m2/s s

experimental testing9 which is expensive and time-consuming. Use of the detailed method described in the present work to derive FRVs should greatly simplify the task of obtaining FRVs for use in LCAs. The dependence of fuel consumption (L/km) on vehicle mass can be represented by the Willans line,10 a classical model of fuel consumption versus power output first developed for steam engines. We present LCA cases for vehicle lightweighting covering combinations of total vehicle or component either with, or without, powertrain resizing. For each case, the MIF, FRV, and fuel consumption for the baseline and lightweighted vehicle or component is mathematically derived based on coast-down coefficients in the EPA vehicle test database. The methods are applied to a grille opening reinforcement (GOR) component based on hypothetical scenarios of replacing steel with either magnesium or carbon-fiber/epoxy (CF/Ep) composite. We compare the use phase fuel consumptions estimated for the GOR component using the MIF and the FRV approaches and discuss the strengths and weaknesses of these methods.

The vehicle dynamics which describe the vehicle loads over a test driving cycle, Pload, are as follows: Pload = Av + Bv 2 + Cv 3 + avM + α

(2)

where v, a, M, and α are vehicle speed (m/s), acceleration (m/ s2), mass (kg), and power demand for accessories, respectively. The values, A (N), B (N/(m/s)), and C (N/(m/s)2) are rolling, rotating, and aerodynamic resistive coefficients, respectively, and are determined by a quadratic fit to the dv/dt versus vehicle speed profile derived from a laboratory measurement of coast down vehicle speed versus time.12 A, B, and C are often called “coastdown” or “target” coefficients and are available in the EPA test database5 for specific vehicle models. Av, Bv2, and avM are the rolling resistance, rotating, and acceleration loads, respectively, and are proportional to vehicle mass. While the associations of coast down coefficients with physical effects above are approximate,12,16 they are useful in calculations of vehicle fuel consumption.12 Integrating the mass-dependent loads over the test schedule gives Fw (L):

2. FUEL CONSUMPTION MODEL The total fuel use in liters, F, to move a vehicle through a drive cycle can be treated as the sum of five fundamental components: F = Fw + Faero + Facc + Ff + Fl

12 12 12 18 18 18 18 18

Fw(L) =

(1)

1 Hf ηiηt

∫

(Av + Bv 2 + avM )dt (3)

Hf, ηi, and ηt, are the heating value of the fuel, thermodynamic efficiency of the engine, and transmission efficiency including drive train losses, respectively. For simplicity, we assume that ηi and ηt are constant although in reality they do change during a driving cycle. Only the positive acceleration load (avM) is considered since a vehicle when idling or decelerating does not require tractive work.17 In eq 1, Cv3 and α are the loads from aerodynamic resistance and accessories, respectively, and are unrelated to vehicle mass. As noted above, the coefficient C primarily represents aerodynamic resistance.12 Integrating over a test schedule provides the fuel used for aerodynamic and accessory loads, Faero + Facc = Fx (L):

where the subscripts w, aero, and acc denote fuel burned to overcome loads associated with moving mass (inertial and rolling resistance), aerodynamic drag, and providing power for accessories, respectively, and f and l denote losses inside the engine (friction and pumping) and miscellaneous losses in the drivetrain, respectively. The descriptions of the five fundamental components are given in equations (S1)−(S6) in the Supporting Information (SI). The energy flows for a typical midsized ICEV are illustrated in SI Figure S1.11−13 The losses Ff and Fl subtract from the fuel that would otherwise be applied to overcoming mass, aerodynamic, and accessory loads. Hence, Ff and Fl are system inefficiencies. Theoretical and empirical studies show that for a given engine speed, Ff is approximately constant and independent of changes in engine output work.10−12,14,15 As seen in SI Figure S1, Fl is more than an order of magnitude smaller than Ff. For convenience we combine Fl and Ff into one term FF, overall friction losses (FF = Ff + Fl) and assume that FF is independent of engine output work. In contrast, the thermodynamic losses are dependent on output work.

Fx(L) =

1 Hf ηi

∫

⎛ Cv 3 ⎞ ⎜⎜ + α⎟⎟dt ⎝ ηt ⎠

(4)

The values and sources of the integration and parameters in eqs 2−4 for the FTP city and highway driving test to calculate Fw and Fx are listed in Table 1. The target coefficients A, B, and C are vehicle specific and can be found in the EPA fuel economy test database,5 the other values in Table 1 are not vehicle specific. 10210

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For weight change with powertrain resizing, since ΔD*/D* =ΔM/M from eq 5,

3. FUEL REDUCTION VALUE MODEL Assessing the benefit of lightweighting involves characterizing the mass dependences of fuel used, and the rate of change of fuel used (dF/dM) upon lightweighting. Lightweighting increases vehicle performance (e.g., increased acceleration) as mass-related loads decrease. This offers an opportunity of reducing powertrain power, i.e., shifting to either a smaller engine or an alternative shift schedule to achieve additional fuel use reduction while maintaining the original performance of a vehicle. For modeling purposes, we rule out scenarios of switching engine type, e.g., from turbo-charged to naturally aspired engine to match vehicle performance. Such scenarios are less scalable than those of resizing engine displacement for performance matching and hence not normally considered in lightweighting LCAs. The performance of a vehicle is often characterized as acceleration capacity or time to reach 60 mph (97 kmph), t0−60, which is determined by the balance between torque demand and power output. In fact, power is the product of torque and engine angular speed. Without changing engine type, vehicle performance, i.e., maximum torque output is characterized by engine displacement and gear ratio (see SI eq S5). In the t0−60 case, the torque demand to move mass, i.e., rolling and inertial resistance, dominates the aerodynamic and accessory power demand.8,19 To maintain vehicle t0−60 performance, the ratio between vehicle mass and maximum torque output or engine displacement should remain constant. ⎛ D ⎞⎛ N ⎞ D* ⎜ ⎟⎜ ⎟ = = const ⎝ M ⎠⎝ V ⎠ M

ΔF = =

=

FRV + =

=

⎛ Fw ⎞ ⎛ ∂F ⎞ ⎜ ⎟ΔM = ⎜ ⎟ΔM ⎝ ∂M ⎠ ⎝M⎠

(5)

(6)

(10)

(11)

In the second approach, we define mass induced fuel consumption as all the changes associated with vehicle mass change (dF/dM), while maintaining vehicle performance. In short, changes in vehicle powertrain are also included. The overall friction loss FF that is dominated by engine size is considered mass-induced, as it changes proportionally to vehicle mass, whereas in the first approach, only a partial overall friction loss, FF((Fw)/(Fw + Fx)) is mass-induced. As Fl ≪ Ff, the mass induced fuel consumption with powertrain resizing, MIF+, is to good approximation the same as FRV with powertrain resizing, FRV+.

⎛ ⎞ ⎛ ⎞ ⎛ ∂F ⎞⎜ 1 ⎟ ⎛ Fw ⎞⎜ 1 ⎟ ⎛ Fw ⎞⎛ FC ⎞ ⎜ ⎟ ⎜ ⎟ = = ⎜ ⎟⎜ ⎟ ⎝ ∂M ⎠⎜ ∫ v dt ⎟ ⎝ M ⎠⎜ ∫ v dt ⎟ ⎝ F ⎠⎝ M ⎠ ⎝ ⎠ ⎝ ⎠

⎛ ⎞⎛ FC ⎞ Fw =⎜ ⎟⎜ ⎟ ⎝ Fw + Fx + FF ⎠⎝ M ⎠

⎛ Fw + Ff ⎞⎛ FC ⎞ ⎛ Fw + Ff ⎞⎛ FC ⎞ ⎟⎜ ⎟ = ⎜ ⎟⎜ ⎟ ⎝ F ⎠⎝ M ⎠ ⎝ Fw + Fx + FF ⎠⎝ M ⎠

⎜

⎛ Fw ⎞⎛ FC ⎞ MIF = ⎜ ⎟⎜ ⎟ ⎝ Fw + Fx ⎠⎝ M ⎠

(7)

The mass rate of change of fuel consumption, units of L/(100 km 100 kg), is often called the fuel reduction value (FRV).6 There are two fuel reduction values depending on whether the powertrain is resized for equivalent vehicle performance. For weight change without powertrain resizing, FRV =

⎛ ΔF ⎞⎛⎜ 1 ⎞⎟ ⎛ Fw + Ff ⎞⎛⎜ 1 ⎞⎟ ⎜ ⎟ ⎟ =⎜ ⎝ ΔM ⎠⎜⎝ ∫ v dt ⎟⎠ ⎝ M ⎠⎜⎝ ∫ v dt ⎟⎠

4. MASS-INDUCED FUEL CONSUMPTION MODEL In a total vehicle LCA, the use phase fuel use corresponds to F in eq 1, which encompasses not only the fuel used to overcome mass related loads, but also aerodynamic resistance, accessory power demand, and overcoming internal system losses, i.e., FF. In a vehicle component LCA, determining the use-phase fuel consumption generally involves separating the mass related fuel consumption from the balance, i.e., those from aerodynamic resistance and accessory power demand when they are normally not affected by the choice of material or design. Clear definition of mass related fuel consumption is particularly important to assign the “baseline” fuel consumption for status-quo design or material of the component. We provide two approaches for computing the mass induced fuel consumption depending on treatment of engine friction losses. In the first approach, the mass induced fuel consumption is defined as the sum of two components: (i) fuel consumed to provide mass dependent work, Fw, and (ii) a share of the fuel consumed to overcome engine friction losses, FF((Fw)/(Fw + Fx)). From this definition, the mass induced fuel consumption for an ICEV is estimated in a driving cycle based on the following formula:4

Without powertrain resizing, ΔD* = 0. Thus, ΔF =

(9)

Equations 8 and 10 can be used with EPA test data to calculate vehicle model specific FRVs and FRV+s. This is illustrated in SI sections S7 and S8 where 83 vehicle model specific results are listed.

⎛ ∂F ⎞ ⎛ ∂F ⎞ ⎜ ⎟ΔM + ⎜ ⎟ΔD* ⎝ ∂M ⎠ ⎝ ∂D* ⎠

⎛ Fw ⎞ ⎛ Ff ⎞ ⎟ΔD* ⎜ ⎟ΔM + ⎜ ⎝ D* ⎠ ⎝M⎠

⎛ Fw + Ff ⎞ ⎜ ⎟ΔM ⎝ M ⎠

Thus, the fuel reduction value with powertrain resizing is as follows:

Here, D = engine displacement (L); N = average engine speed (r/s); V = average vehicle speed (m/s), N/V = gear ratio (r/m); and D* = powertrain size, product of engine displacement (D) and gear ratio (N/V). The mathematical derivation starts with expressing the change in fuel use ΔF, in terms of change in mass, ΔM, and powertrain size, ΔD*, from SI eqs (S1)−(S6): ΔF =

⎛ Fw ⎞ ⎛ Fw ⎞ ⎛ Ff ⎞ ⎛ Ff ⎞ ⎟ΔD* = ⎜ ⎟ΔM ⎜ ⎟ΔM + ⎜ ⎟ΔM + ⎜ ⎝ D* ⎠ ⎝M⎠ ⎝M⎠ ⎝M⎠

(8)

where FC is the fuel consumption rate in units of L/km (= 2.35/ fuel economy in mpg) measured in the fuel economy test, i.e. FC = (F/d) where d = ∫ v dt or distance driven.

MIF+ =

⎛ Fw + FF ⎞⎛ FC ⎞ ⎛ Fw + Ff ⎞⎛ FC ⎞ + ⎜ ⎟⎜ ⎟⎜ ⎟ ≅ ⎜ ⎟ = FRV ⎝ F ⎠⎝ M ⎠ ⎝ F ⎠⎝ M ⎠ (12)

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Figure 1. Fuel consumption (L) with unadjusted (F) or adjusted powertrain (F+). M, d, FF, Fx, and Fl, represent vehicle mass, driving distance, overall friction loss, and fuel consumption from aerodynamic and accessory loads, and miscellaneous losses in the drivetrain, respectively. The slopes normalized by driving distance are FRV and FRV+ without and with powertrain resizing, respectively. The filled circle is the baseline vehicle.

Table 2. Summary of Use-Phase Fuel Consumption (L) with/without Powertrain Adjustment for Baseline and Lightweighted Vehicle and Component system

powertrain resizing

baseline metric

use-phase fuel consumption (L)

equation # in text

baseline vehicle

F

F(M1) = FC·d

13

baseline component

MIF

fb (m1) = MIF(M1)·m1·d

14a

FRV

f (m1) = FRV·m1·d

14b

F(M 2) = F(M1) − FRV·ΔM·d

lightweighted vehicle

lightweighted component

no

F

yes

F

F (M 2) = F(M1) − FRV ·ΔM·d

17

no

MIF

fl (m2) = fb (m1) − FRV·Δm·d

16

yes

MIF

f l+ (m2) = fb (m1) − FRV +·Δm·d

18

no

FRV

f (m2) = f (m1) − FRV·Δm·d

19

+

We note that while MIF is a function of vehicle mass (M), FRV, FRV+, and MIF+ are constant as shown in SI Figure S2. Equations 11 and 12 can be used with EPA test data to calculate vehicle model specific MIFs and MIF+s. This is illustrated in SI sections S7 and S8, which list 83 vehicle model specific results.

15

+

F(M1) = FC·d

(13)

where FC is fuel consumption (L/km), and d is distance driven (km). The fuel consumption (L) of a baseline component, f b(m1), accounts only for fuel consumption attributable to mass (assuming the component is unrelated to aerodynamic and accessory power demand). Thus, the baseline fuel consumption (L), f b(m1), can be written as follows:

5. FUEL CONSUMPTION WITH LIGHTWEIGHTING Here, we present a method of calculating the use phase fuel consumptions for lightweighted vehicles and components based on the MIFs and FRVs of a reference vehicle. In Figure 1, the fuel consumption (L) F and F+ over a driving cycle for powertrain unadjusted and adjusted lightweighting, respectively, are plotted against vehicle mass, M (kg). Line F is adapted from the Willans line where the fuel consumption rate for the internal combustion engine is described as a linear function of power demand.11,12,15,20 FF is the energy loss from engine friction discussed above. When the powertrain is not adjusted, FF does not change with lightweighting. We consider two levels of lightweighting; vehicle lightweighting from M1 to M2 and component lightweighting from m1 to m2. For the component lightweighting cases, we assume that the vehicle mass change from m1 to m2 is the same as that from M1 to M2 (M1 − M2 = m1 − m2). The fuel consumption (L) of the baseline vehicle, F(M1), includes both fuel consumptions related to mass and those unrelated to mass as shown in eq 1. Thus,

fb (m1) = MIF(M1) ·m1·d

(14a)

If the second approach of the mass induced fuel consumption is employed as in eq 12, then MIF(M1) would be replaced by MIF+ in eq 14a. The baseline fuel consumption of a component can also be written in terms of a fuel reduction value, i.e., f (m1) = FRV ·m1·d

(14b)

From Figure 1, the use phase fuel consumption (L) of the lightweighted vehicle, F(M2) or component f l(m2) can be determined by subtracting the fuel reduction attributed to the mass change from the baseline fuel consumption. Thus, F(M 2) = F(M1) − FRV ·ΔM ·d

(15)

fl (m2) = fb (m1) − FRV ·Δm ·d

(16) +

When powertrain is resized, FRV replaces FRV in eqs 15 and 16. 10212

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Environmental Science & Technology Table 3. Grille Opening Reinforcement (GOR) Mass and Cradle-to-Gate GHG Emissions material

part mass (kg)

vehicle mass (kg)

GHG (kgCO2eq/kg) from cradle-to-gate

steel magnesium

6.2 3.2

1700 1697

5.1 27.3

carbon fiber/ epoxy

2.7

1696.5

20.8

note stamped galvanized primary steel primary Mg from Pidgeon process; die casting cover gas − SO2 carbon fiber 30 wt %

source GREET 20143 Ehrenberger 201321 GREET 20143

Figure 2. Life cycle GHG emissions for steel, Mg, and CF/Ep designs of the GOR component for a vehicle lifetime of 160 000 miles (=257 500 km) with and without powertrain (PT) resizing.

F +(M 2) = F(M1) − FRV +·ΔM ·d

(17)

f l+ (m2) = fb (m1) − FRV +·Δm ·d

(18)

although the GOR designs are real, the applications discussed here are hypothetical. For simplicity, secondary mass reduction opportunities afforded by the primary mass reduction are not considered in the present analysis. The mass of each component and the greenhouse gas (GHG) emissions from material production through component manufacturing, i.e., cradle-togate are listed in Table 3. A wide range of GHG emissions factors are reported in the literature for Mg and CF/Ep components.2 As discussed elsewhere,1 this range reflects different assumptions for recycling and for energy consumption during materials production. Our purpose here is neither to revisit this discussion nor to compare across materials, but to demonstrate the utility of the model in our study to estimate the use-phase fuel consumption. We provide an analysis of the life cycle GHG emissions for the baseline steel GOR component and two potential lightweight GOR components hypothetically applied to the 2013 model year (MY) Ford Fusion, which has an equivalent test weight of 1700 kg and an unadjusted, EPA city-highway combined fuel economy of 34.6 miles per gallon (6.795 L/100 km). According to the EPA fuel economy database,5 the coast-down coefficients A, B, and C are 85.9 N, 5.23 N/(m/s), 0.306 N/(m/s)2. The MIF, FRV, and FRV+ (∼MIF+) calculated from eqs 11, 8, and 10 and the parameters and constants in Table 1 are 0.283, 0.202, and 0.316 L/(100 km 100 kg), respectively. SI Section S5 provides the detailed calculation steps for MIFs and FRVs. The use-phase fuel consumption and the calculation steps for each case are listed in SI section S6, based on a lifetime driving distance of 160 000 miles (257,500 km) and the well-to-wheel (fuel production and vehicle operation) GHG emissions factor of

If eq 14b is used for the baseline, then the fuel consumption (L) of the components is written as follows: f (m2) = f (m1) − FRV ·Δm ·d

(19)

In the case of lightweighting (Δm) with a powertrain adjustment, the fuel consumption of a component is the same as f(m2). This is a result of the FRV model being a causal approach. FRV (Fw/M) is the mass rate of change of F and can be measured at any time before or after a powertrain adjustment from a series of track tests to get dF/dM. As per SI eqs (S2) and (S5), FRV does not change with a powertrain adjustment. However, FRV+ is a pseudo or empirical mass rate of change of F, a combination of both mass (∂F/∂M) and powertrain (∂F/∂D*) rates of change of F, and is useful for calculating overall fuel consumption for the vehicle for those changes. Table 2 summarizes the formulas for the use-phase fuel consumption for each case. See SI sections S4 and S5 for complete calculation methods of use phase fuel consumption depending on LCA system definition and powertrain resizing.

6. APPLICATION TO GRILLE OPENING REINFORCEMENT The use-phase fuel consumption estimation methods for ICEVs in this study are applied to lightweighting scenarios for a grille opening reinforcement (GOR). Two lightweighting materials, magnesium (Mg) and carbon fiber/epoxy composite (CF/Ep), are considered to replace the standard steel design. We note that 10213

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Figure 3. Comparison of life cycle GHG emissions calculated for the steel and magnesium GOR designs using the MIF, FRV, and Savings fuel consumption accounting methods for 160 000 miles (=257 500 km) of lifetime driving distance. PT = powertrain. Changes in GHG emissions and percent changes (%) relative to the baseline are indicated above the bars for MIF and FRV. The numbers in square brackets in the x-axis labels are the equations in the text used for the calculations. Net changes in GHG emissions (cradle to gate + use phase) are indicated above the bars for the Savings approach.

based on generic values for FRV and FRV+ to calculate fuel savings from lightweighting. We refer to this below as the “Savings method”. For the Savings method, generic FRVs of 0.38 and 0.16 L/(100 km 100 kg) with and without powertrain resizing, respectively, from Koffler (2014)23 are used. As seen in the three left-hand bars in Figure 3, the MIF method captures the absolute and relative benefit of lightweighting by providing GHG emissions for both the baseline (steel) and lightweighted (Mg) designs and by differentiating powertrain resizing options. The MIF method estimates a 11 kg CO2-eq increase and 15 kg CO2-eq decrease of life cycle GHG emissions, without and with powertrain resizing, respectively. As expected based on the equations in Table 2, the FRV method gives the same result as the MIF method without powertrain resizing; a 11 kg CO2-eq increase. As discussed in section 5, the FRV method gives the same values for component GHG emissions for scenarios with and without powertrain adjustments. The higher percentage increase for the FRV method (9% versus 7%, see Figure 3) for the same absolute increase (+11 kg CO2-eq ) reflects the lower baseline fuel consumption in the FRV method (124 versus 162 kg CO2-eq ). The two right-hand bars in Figure 3 are results from the Savings method using generic FRVs from Koffler (2014),23 the net GHG emission changes are −29 and +20 kg CO2‑eq. The cradle-to-gate portion of the bars is the change in replacing the steel with Mg component. The negative use phase bars are the savings calculated from the 3 kg weight reduction using FRV = 0.16 and FRV+ = 0.38 L/(100 km 100 kg). The difference between the powertrain resizing cases for the MIF and Savings methods, −15 versus −29 kg CO2-eq , stems from the different FRV+ values used in each method, 0.316 versus 0.38 L/(100 km 100 kg). Similarly, the difference in the without powertrain resizing results +11 versus +20 kg CO2-eq stems from the different FRV values used in each method, 0.202 versus 0.16 L/ (100 km 100 kg). While the FRVs in the MIF method correspond to specific vehicle models, those used in the Savings approach by Koffler and Rohde−Brandenburger (2010)22 are for

2874 g CO2-eq/liter of gasoline in The Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model.3 From a total vehicle perspective, the 3.0− 3.5 kg weight reduction has a very small (∼0.1%) impact on the use-phase fuel consumption. However, from a component perspective, the use-phase fuel savings are substantial at approximately 40−60% depending on the LCA method used and the powertrain resizing scenario. Adding the cradle-to-gate to the use-phase emissions discussed above gives the life cycle GHG emissions of the steel, Mg, and CF/Ep grille opening reinforcement components in Figure 2. The white bars are the use-phase fuel consumptions calculated using the MIF method. The Mg design has higher life cycle GHG emissions than the CF/Ep design because of energy and GHG intensive smelting and refining processes.21 For the MIF baseline with powertrain resizing, the Mg and CF/Ep designs have 9% and 36% lower life cycle GHG emissions than the steel design. Without powertrain resizing, the CF/Ep design has 17% lower life cycle GHG emissions than the steel design, but the Mg design has 7% higher life cycle GHG emissions than the steel design. As shown in Figure 2, powertrain resizing is a critical factor in determining the lifecycle benefit of lightweighting. However, the relative values of steel vs an alternative’s GHG emissions for material production as well as masses of each needed to meet part or component specifications are also important. Clearly, the 3.0− 3.5 kg weight reduction considered here would not justify powertrain resizing. However, simultaneous changes in many small parts as part of a holistic design can justify powertrain resizing. Figure 3 compares the implications of the use-phase fuel consumption methods for component lightweighting LCA using the magnesium option described above for the 2013 MY Fusion. We refer to the approach in eqs 14a, 16, and 18 as the “MIF method”, while for the approach in eqs 14b and 19, we refer to this as the “FRV method”. For brevity, the case with MIF+ is not analyzed. The method described by Koffler and Rohde− Brandenburger (2010)22 uses an avoided impact approach 10214

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Article

Environmental Science & Technology

The disadvantages of ignoring model-specific effects can be remedied if a model specific FRV is calculated using the procedure described in the present work. The Savings method is focused on understanding changes from a vehicle level and does not define the fuel consumption of the baseline or lightweighted components. The FRV method is intermediate in complexity, provides values for the fuel consumption of the baseline and lightweighted components, but does not distinguish between scenarios with and without powertrain adjustments. The MIF method is the most complex of the three but provides results for all four combinations of vehicle and component perspective with, and without, powertrain adjustment. LCA practitioners need to select the method that meets their needs. Comparing the methods listed in Table 2, the key difference in lightweighting LCA methods stems from the metric of “baseline” fuel consumption (MIF or FRV). MIF (L/km kg) is the amount of fuel (L) used to move a mass (kg) for a distance (km) in a driving cycle as opposed to the fuel used to overcome aerodynamic resistance and to provide accessory power demand. Taking into account thermodynamic, transmission, and engine friction losses as fuel consumption, MIF values are consistent with total energy efficiency of modern ICEVs of ∼20% in literature11,13,17,24,25 (see SI Figure S1). FRV is the fundamental mass−fuel relation (dF/dM) and does not include engine friction loss (FF) as it remains unchanged upon mass change without adjusting powertrain. Thus, from eqs 8 and 11:

generic vehicles and based on somewhat different assumptions on parameters, e.g., transmission efficiency of 0.95 in Koffler (2014) versus 0.88 in Table 1. Finally, we explored the life cycle benefit of the Mg GOR design compared to the baseline steel design for 83 different ICEVs based on their MIF, FRVs, and mass (M). The MIF, FRV, and FRV+ for these vehicles are given in SI section S7 and are in the ranges 0.22−0.43, 0.15−0.26, and 0.27−0.53 L/(100 km 100 kg), respectively. As shown in Figure 4, with powertrain resizing,

FRV =

⎛ F − FF ⎞ ⎜ ⎟MIF ⎝ F ⎠

(20)

In the FRV method, engine friction (FF) is considered as inherent energy use neither induced by mass nor aerodynamic drag. MIF can be calculated from vehicle parameters such as rolling coefficient (CR) and aerodynamic drag coefficient (CD) or from coast-down coefficients in the EPA test database as discussed in this study. FRV can be measured directly in a vehicle test by removing mass.9 We show here that FRV can also be calculated using vehicle parameters/coefficients from the EPA test database,5 similarly to MIF (see the numerical examples given in SI sections S7 and S8. We note that the fuel economies in the EPA test database used in the present analysis are unadjusted values based on the FTPCity and highway cycles and are higher than those from EPA Fuel Economy Guide5,26 which appear on the fuel economy label. Label fuel economies are based on the EPA 5-cycle test which includes the US06, SC03, and Cold-FTP cycles to better represent real-world fuel economy and are approximately 10− 30% lower than those based on the FTP-city and highway cycles. Use of the 5-cycle fuel economy will result in higher MIFs and FRVs as can be inferred from eqs 8, 10, and 11 (see SI sections S7 and S8 for comparison). As illustrated in Figure 4, the lifecycle impact of lightweighting is critically dependent on three factors: (i) powertrain resizing, (ii) baseline vehicle MIF (MIF+), and (iii) relative material production burdens of replaced and substituted materials. The first factor is intuitive and well-known.5,6,15,16 The second factor is not well-known. Using the MIF method, we are able to demonstrate and quantify the importance of vehicle model specific effects (see Figure 4). The third factor highlights the trade-off typically encountered between a decrease in vehicle fuel consumption and an increase in material production burdens upon lightweighting a vehicle by substituting an alternative material for steel.

Figure 4. Change in GOR component life cycle GHG emissions (%) vs baseline MIF upon replacing steel with Mg design for 2013 model year vehicles with (filled symbols), and without (gray symbols), powertrain resizing.

the life cycle GHG of the Mg GOR design decreases between 3% and 27%. Without powertrain resizing, the life cycle GHG emissions change between −1% and 17%; the Mg GOR design can result in reduced or increased global warming impact. The wide range of these results and the fact that they include both positive and negative numbers emphasizes the importance of including values for MIF and FRVs based on specific rolling (A), rotational (B), and aerodynamic (C) resistive coefficient of the vehicle model in question.5 Inspection of Figure 4 shows that lightweighting benefit increases with MIF. Vehicles with high fuel consumption (low fuel economy) and high power tend to have high MIF values4 and benefit most from lightweighting.

7. DISCUSSION The present work provides a mathematical framework accounting for the benefits of vehicle lightweighting in LCAs. We show how to calculate vehicle model specific FRVs and MIFs from the publically available vehicle test data and how to use these parameters in lifecycle assessments from vehicle and component perspectives both with and without powertrain resizing. We show that the Savings, FRV, and MIF accounting methods provide a consistent picture of the lifecycle benefits of lightweighting. Our goal here is not to recommend one of these methods over the others but to illustrate their use and their advantages and disadvantages. The Savings approach using a generic FRV has the advantage of simplicity, as it eliminates the need to calculate a FRV and the need to define the fuel consumption of the baseline component. 10215

DOI: 10.1021/acs.est.5b01655 Environ. Sci. Technol. 2015, 49, 10209−10216

Article

Environmental Science & Technology

(8) Wohlecker, R.; Wallentowitz, H.; Johannaber, M.; Espig, M.; Leyers, J. Determination of Weight Elasticity of Fuel Economy for Conventional ICE Vehicles, Hybrid Vehicles and Fuel Cell Vehicles; Forschungsgesellschaft Kraftfahrwesen mbH: Aachen, Germany, 2007. (9) Carlson, R.; Lohse-Busch, H.; Diez, J.; Gibbs, J. The Measured Impact of Vehicle Mass on Road Load Forces and Energy Consumption for a BEV, HEV, and ICE Vehicle. SAE Int. J. Alt. Power. 2013, 6 (1), SAE 2013−01−1457. (10) Willans, P. W. Economy trials of a non-condensing steam-engine: simple, compound and triple. Minutes of the Proceedings of the Institution of Civle Engineers 1888, 93, 128−188. (11) Ross, M. Fuel Efficiency and the Physics of Automobiles. Contemp. Phys. 1997, 38 (6), 381−394. (12) Nam, E. K.; Giannelli, R. Fuel Consumption Modeling of Conventional and Advanced Technology Vehicles in the Physical Emission Rate Estimator (PERE); EPA420-P-05−001; U.S. Environmental Protection Agency: 2005. (13) Lutsey, N. A technical analysis of model year 2011 US automobile efficiency. Transport. Res. D-TR. E 2012, 17, 361−369. (14) Heywood, J. B. Internal Combustion Engine Fundamentals; McGraw-Hill: 1988. (15) Ross, M.; An, F. The Use of Fuel by Spark Ignition Engines; SAE International Congress and Exposition, Society of Automotive Engineers, March 1; Detroit, MI: 1993. (16) Sovran, G.; Blaser, D. Quantifying the Potential Impacts of Regenerative Braking on a Vehicle’s Tractive-Fuel Consumption for the U.S., European, and Japanese Driving Schedules. SAE 2006−01−0664. In SAE World Congress, Detroit, MI, 2006.10.4271/2006-01-0664 (17) An, F.; Santini, D. J. Mass Impacts on Fuel Economies of Conventional vs. Hybrid Electric Vehicles. 2004 SAE World Congress, SAE International, March 8−11; Detroit, MI: 2004. (18) US EPA. Dynamometer Drive Schedules http://www.epa.gov/ nvfel/testing/dynamometer.htm (accessed March 2014). (19) US EPA. Light-Duty Automotive Technology, Carbon Dioxide Emissions, and Fuel Economy Trends: 1975 Through 2012; EPA-420-R13−001; 2013. (20) Ross, M. Automobile Fuel Consumption and Emissions: Effects of Vehicle and Driving Characteristics. Annu. Rev. Energy Env. 1994, 19, 75−112. (21) Ehrenberger, S. Life Cycle Assessment of Magnesium Components in Vehicle Construction; DLR: 2013. (22) Koffler, C.; Rohde-Brandenburger, K. On the calculation of fuel savings through lightweight design in automotive life cycle assessments. Int. J. Life Cycle Assess. 2010, 15, 128−135. (23) Koffler, C. Life cycle assessment of automotive lightweighting through polymers under US boundary conditions. Int. J. Life Cycle Assess. 2014, 19, 538−545. (24) Committee on the Assessment of Technologies for Improving Light-Duty Vehicle Fuel Economy Assessment of Fuel Economy Technologies for Light-Duty Vehicles; The National Academy Press: National Research Council of the National Academies: Washington, DC, 2011. (25) U.S. Department of Energy. Where the Energy Goes: Gasoline Vehicles. http://www.fueleconomy.gov/feg/atv.shtml (accessed September 2014). (26) Model Year 2013 Fuel Economy Guide; U.S. Department of Energy and U.S. Environmental Protection Agency: 2013.

Lightweighting is an important technology which is being adopted by vehicle manufacturers to improve vehicle fuel economy. As illustrated here, combining data from the EPA database5 with the MIF/FRV model described in this study can provide vehicle model specific lifecycle assessments of the benefits of lightweighting from both a total vehicle and a component perspective with, and without, powertrain resizing. Using this vehicle-specific approach rather than adopting generic FRV values, or ranges of values, should improve the accuracy in characterizing the use phase benefits of vehicle lightweighting in future LCA studies.

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ASSOCIATED CONTENT

S Supporting Information *

Detailed calculation steps and results, Tables S1−3, and Figures S1−3. The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.5b01655.

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AUTHOR INFORMATION

Corresponding Author

*Phone: 313-323-9745; e-mail: [email protected] (H.C.K.). Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS Ford Motor Company (Ford) does not expressly or impliedly warrant, nor assume any responsibility, for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe the rights of third parties. Reference to any commercial product or process does not constitute its endorsement. This article does not provide financial, safety, medical, consumer product, or public policy advice or recommendation. Readers should independently replicate all experiments, calculations, and results. The views and opinions expressed are of the authors and do not necessarily reflect those of Ford. This disclaimer may not be removed, altered, superseded or modified without prior Ford permission. This research was supported in part by the U.S.−China Clean Energy Research Center (CERC) on Clean Vehicles. The CERC is partially supported by the U.S. Department of Energy (Award No. DE-PI0000012) and its industrial partners.

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REFERENCES

(1) Keoleian, G. A.; Sullivan, J. L. Materials challenges and opportunities for enhancing the sustainability of automobiles. MRS Bull. 2012, 37 (April), 365−372. (2) Kim, H. C.; Wallington, T. J. Life-Cycle Energy and Greenhouse Gas Emission Benefits of Lightweighting in Automobiles: Review and Harmonization. Environ. Sci. Technol. 2013, 47, 6089−6097. (3) GREET Model. Transportation Research and Analysis Computing Center, Argonne National Laboratory. Argonne, IL, 2014. (4) Kim, H. C.; Wallington, T. J. Life Cycle Assessment of Vehicle Lightweighting: A Physics-Based Model of Mass-Induced Fuel Consumption. Environ. Sci. Technol. 2013, 47, 14358−14366. (5) US EPA. Emissions and Fuel Economy Test Data http://www.epa. gov/otaq/tcldata.htm (accessed March 2014). (6) Ridge, L. EUCAR - Automotive LCA Guidelines - Phase 2. Total Life Cycle Conference and Exposition, Society of Automotive Engineers, December 1−3; Graz, Austria: 1998. (7) Eberle, R.; Franze, H. A. Modelling the Use Phase of Passenger Cars in LCI. Total Life Cycle Conference and Exposition, Society of Automotive Engineers, December 1−3; Graz, Austria: 1998. 10216

DOI: 10.1021/acs.est.5b01655 Environ. Sci. Technol. 2015, 49, 10209−10216