10/3/2011 DRAFT – DO NOT CITE OR QUOTE For NPC Study Discussion Only 1 FTF Coordinating...

DRAFT – DO NOT CITE OR QUOTEFor NPC Study Discussion Only

110/3/2011

FTF Coordinating Subcommittee Meeting Model Structure Discussion

Deanne Short

October 12, 2011

1


210/3/2011

Modeling Methodology Overview

Inputs from Study Step 1(a)

• Vehicle technology costs• Vehicle attributes• Fuel and infrastructure

technology costs• Fueling infrastructure attributes• Biofuel supply curves

Other inputsAEO2010 oil price scenariosGHG factors for fuelsFueling infrastructure cost analysis

a) Inputs selected from ranges of values defined by the literature reviewed in Step 1 of the Studyb) Determines vehicle attributes (mpg, vehicle cost) based on fuel and vehicle technology costs consistent with payback criteria in VCMc) Estimates market share of new light duty (LD) vehicle sales based on vehicle attributes and vehicle/fuel costsd) Tracks LD vehicle stocks, stock fuel efficiency, fuel consumption (by type), fuel expenditures, VMT and GHG emissions by year

Outputs for Analysis• Fuel Consumed by Type per Year• GHG Emissions (tCO2/year)• Fleet Share of Vehicles by Type• Vehicle Cost of Fleet (cents/mile)• Fuel Cost (cents/mile)• Dispensing Infrastructure

Investment• Vehicle Miles Traveled

VehicleChoiceModel(c)

VISION Tool(d)

VehicleAttributeModel(b)

Vehicle &Fuel attributes

Mkt. share by yearfor new sales

Fuels & Infracost

analysis


310/3/2011

Choice Variables Selected Under Various Assumptions

• Vehicle costs and fuel efficiencies were posited under combinations of cost assumptions – Vehicle technology high and low cost functions

• Covers aerodynamics, tires, light weighting, etc. used by all Subgroups• For liquid ICE vehicles, includes power train and hybridization

– Specific technology high and low cost functions• For electric, includes energy batteries• For CNG, includes fuel storage, engine systems and production pathways• For fuel cells (FCEV), includes fuel cell system, fuel storage and power battery

– Specific dispensing high and low cost functions which were factored into the fueling or charging costs

• For electric, vehicle costs and fuel efficiencies were posited assuming residential charging alone and residential plus public charging

• For FCEV, vehicle costs and fuel efficiencies were posited assuming high and low dispensing cost estimates, which were incorporated into the gasoline gallon equivalent cost of fueling

• For CNG, vehicle costs and fuel efficiencies were posited assuming fuel prices that linked gas feedstock prices to oil prices, and a mix of dedicated new and upgraded fuel dispensing infrastructure

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410/3/2011

Diversity in Studies Led to a Set of 384 Possible Future States

Vehicle Technology

Costs

Specific System Costs

Fuel dispensing

or charging

costs

Sets of inputs

(Product of three

components)Liquid ICEs 2 1 1 2CNG 2 2 1 4Electrics 2 2 2 8Fuel Cell EV 2 2 2 8

Combinations 2* 8 4 64192384

*All subject to same vehicle technology cost curve simultaneously

Oil Price Cases - 3xBiofuel Cases - 2x

• The diverse cost estimates in published data led the Subgroups to posit multiple sets of vehicle costs and fuel efficiencies under 3 fuel or charging cost scenarios derived from the AEO2010 oil price cases

• Evaluating the impact of the inputs required analyzing 64 combinations of the inputs under each of the 3 oil price scenarios and under the possibility of high or low biofuel availability

• To reflect uncertainty in outcomes, inputs were mapped to outputs using VCM and VISION

Independent Subgroup inputs for each oil price case

Possible combinations

4DRAFT – DO NOT CITE OR QUOTE

For NPC Study Discussion Only


510/3/2011

Integration Tool: Vehicle Choice Model (1 of 3)

• Vehicle choice model (VCM) is a spreadsheet tool that applies a system of nested multinomial logit (NMNL) functions to calculate new vehicle market shares across fuel/vehicle options. The coefficients and functional forms are taken from AEO 2010.

• VCM estimates market share based on the following attributes– Price of vehicle

– Fuel cost of a mile (price of gasoline gal equivalent/mpg, so input fuel price and mpg)

– Range (distance between refueling)

– Acceleration (seconds 0-60mph; function of hp & wt)

– Luggage space (% of Liquid ICE)

– Maintenance cost

– Make/model Availability (variety of models w/tech)

– Fuel availability (% fueling stations w/particular fuel)

– Home refueling option for EVs

• Attributes are weighted by coefficients that reflect the marginal (negative) dollar value of an attribute. The sum of the weighted attributes is a generalized cost of the fuel/vehicle option

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610/3/2011


• Only vehicle price and fuel cost of a mile are being varied across fuel/vehicle options. – Other attributes are set equal to the reference case conventional values.

– The implicit assumption is that in the long run, at commercial volumes, the other attributes will equalize across technology pathways.

– The analysis will identify whether an alternative technology is competitive on a pure vehicle and fuel cost basis in the long run

• Outputs of the model do not provide insights on the transition to alternative technologies.– New vehicle market shares in each year are mature commercial volumes.

This follows from equalizing the fuel availability and make/model availability attributes, along with fuel cost assumptions built on fully burdened dispensing infrastructure.

– The study’s discussion on transition may use insights from the model by altering these attributes.

– VCM is also capable of imposing upper bound constraints on market shares by specifying s-curve parameters. S-curves are not active constraints in the most recent model runs.


710/3/2011


• For consistency with VCM, the vehicle attribute model minimizes the cost of driving over 47,500 miles.– The VCM coefficients on vehicle cost (Cv) and fuel cost of a mile (Cf) imply

incremental vehicle cost increases (vc) must be offset by lower fuel cost of a mile (fc) over 47,500 miles for no change in the generalized cost of the fuel/vehicle option.

f = Cv * vc + Cf * fc + …

Cv * vc = Cf * fc for f=0

vc = Cf /Cv * fc

As an example, the vehicle cost coefficient for small cars is -0.0000131 and the fuel cost coefficient is -0.62159. The ratio, Cf /Cv, equals 47500.

The coefficients for the other classes are different, but the ratios are all 47500.


810/3/2011

VCM to VISION

• The market shares, fuel mpg, fuel cost per gge, and percent splits for multi-fuel vehicles from VCM are entered into VISION case by case– VCM aggregates the 5 size class market shares and fuel mpgs into

autos and light truck

• VISION calculates the impact of the technology pathway mix on fuel consumption, GHG and VMT.– VISION contains fleet assumptions, VMT and carbon coefficients– A vehicle value calculation was added to VISION to get a fleet total

cost of driving

• We loaded VISION with the high and low oil price cases from AEO 2010, thus there are 3 VISION and VCM files in our set of tools


910/3/2011

Back-up


1010/3/2011

Modeling Flow Detail (Light Duty Fleet)

Vehicle Attribute Model

InfrastructureSpreadsheet

Vehicle Choice Model (VCM)

VISION Tool (1st iteration)

High/Low Retail Fuel Cost ($/GEG)

High/Low SpecificVehicle Tech. Cost

Common VehicleTech. Attributes

All vehicle attrib.,mpg, vehicle cost% fuel split formulti-fuel vehicles

Mkt. shares of new autos & LT by tech;Fuel economy of new autos & LT

Assumes “0” biofuel in 1st iteration

BiofuelVolumes Calc.

Fuel volumes (BTU/year)

VISION Tool (2nd iteration)

Gasoline /Diesel Price

in Case

Biofuel volume;“XX” in Bxx Blend

GHG emissions by yearVMT by Vehicle TechnologyBTU by fuel typeFleet vehicle & fuel cost of drivingFuel efficiency of fleet

InfrastructureAccounting

Infrastructure portion of retail cost ($/GEG)

max fuel consumption (GEG)

Total Infrastructure cost (2008 $ billions)

BiofuelScenario

(High/Low)

as of 10/3/11

Cost of new vehiclesFuel cost of driving of new vehicles


1110/3/2011

S-curve specifications

Market Penetration Limitation CurvesS-Curve may be applied as a maximum achieveable market penetration or as a factor that scales calculated demand.Curve is applied to final shares, NOT within logit nests. Deferred share is re-allocated among all other (unlimited) technology types with market share.

Method: Apply curve as: 1 = maximum market penetrationShape Coefficient (k2) for All Curves: 5

TechnologySmall

CarLarge

Car Pickups

Small SUVs and

Minivans

Large SUVs and

Standard Vans

Addl HEV limits

appd in NMNL

level 2§

Maximum Value of S-Curve at Saturation (k1)*Conventional 1.00 1.00 1.00 1.00 1.00TDI 1.00 1.00 1.00 1.00 1.00PHEV10 1.00 1.00 1.00 1.00 1.00 1.00PHEV40 1.00 1.00 1.00 1.00 1.00 1.00ETOH flex 1.00 1.00 1.00 1.00 1.00CNG 1.00 1.00 1.00 1.00 1.00Electric 0.50 0.50 0.50 0.50 0.50Gasoline HEV 1.00 1.00 1.00 1.00 1.00H2 FCV 1.00 1.00 1.00 1.00 1.00Tech 9 1.00 1.00 1.00 1.00 1.00Tech 10 1.00 1.00 1.00 1.00 1.00

Years to Half Saturation (k3)Conventional 0 0 0 0 0TDI 3 3 3 3 3PHEV10 6 6 6 6 6PHEV40 6 6 6 6 6ETOH flex 5 5 5 5 5CNG 10 10 10 10 10Electric 10 10 10 10 10Gasoline HEV 5 5 5 5 5H2 FCV 10 10 10 10 10Tech 9 10 10 10 10 10Tech 10 10 10 10 10 10

* Enter a value between 0 and 1.0; enter "0" to remove the technology from the market

0.0000

0.1000

0.2000

0.3000

0.4000

0.5000

0.6000

0.7000

0.8000

0.9000

1.0000

0 5 10 15 20 25 30

Years Since Initial PenetrationS-

Curv

e Va

lue

Conventional

TDI

PHEV10

PHEV40

ETOH fl ex

CNG

Electric

Gasol ine HEV

H2 FCV

Tech 9

Tech 10

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