electric vehicles will barnard pam becker troy “hugin” noble linda sonne jonathan weiss...
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What are EV’s?TRANSCRIPT
ELECTRIC VEHICLES
•Will Barnard•Pam Becker•Troy “Hugin” Noble•Linda Sonne•Jonathan Weiss•Christian Wiest•Ted Yu
Coming soon to your everyday life!
Agenda
• EV Overview• EV Value Proposition• Bayesian Network Overview• Results and Sensitivity• Limitations of Model• Recommendations
What are EV’s?
Why should people like driving an EV?
• Quiet, Clean Driving Experience• High Performance• Lower Operating Costs • No Gas Stations - Refuel Where You Are!• Environmentally Friendly• Energy Security
But are they safe?
Where can I charge?How long will it take?
How far can I go?
What is the cost?
• Vehicle– Purchase– Lease– Subsidies
• Ownership– Battery Replacement– Wear and Tear
• Refueling
Consumer Sensitivity
Minimum Efficient Scale: 60% AcceptancePrice: $1,000 PremiumRange: 100 miles
Stackeholders Parties Interests
Consumers Individual, Rental, CorporateFleet, Public Transportation
Performance Total Cost of Ownership Convenience
Ecological EPA, Sierra Club, WorldPopulation
Environmental protection
Petroleum Stakeholders Gas Stations, ForeignGovernments
Continue world dependenceon fossil fuels
Electric Stakeholders Battery Manufacturers, PublicUtilities,
New sources of revenue Technological gains Efficient use of available
capacity
Political Stakeholders Local, National, and ForeignGovernments
Decrease dependence onforeign resources
Serve constituents
Car Manufacturers World Manufacturers, NewVentures
Profitable production Servicing consumer demand
Stakeholders
Bayesian Network:
Consum er Dem and Manuf. Investm entR&D and Capital
Governm entRequirem ents
Governm entAssistance
E lectic VehicleSupply
Problem Statement:
Determine the probability of success of EV’s for an existing car manufacturer.
Network Weights
E d u ca tion &In fo rm ation
V alu eP rop os it ion
S oc ie ta lA ccep tan ce
C on su m er D em an d
E con om ics
P artn e rs h ip s &A llian ces
S u c cess o fC om p etito rs
M an u f. In ves tm en tR & D an d C ap ita l
L ob b yin g
G lob a lR eg u la tion s
D om es ticR eg u la tion s
G overn m en tR eq u irem en ts
A n ti-tru s tL aws
P aten ts
S u b s id ies
G overn m en tA ss is tan ce
E lec tic V eh ic leS u p p ly
0.35 0.20 0.20 0.15
Results and Sensitivity Analysis
• ResultsResults: Probability (Supply = High) = 54.79%
• SensitivitySensitivity:– If Consumer Demand has 100% probability of being
high:Probability (Supply = High) = 69.94%
– If Consumer Demand has 100% probability of being low: Probability (Supply = Low) = 34.94%
Limitations of model
• Dilution of probabilities given high number of hierarchy levels
• Independence of probabilities• Definition of influence weights • Constraint of two states of nature per node• Lack of consideration of time shifts
Recommendations• Investment
– Prioritize according to influence of primary nodes– Create an implementation timeline
• Demand– Continue to monitor external influences
• Stakeholders– Partner for lobbying and product development