Electric vehicles
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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.

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Electric vehicles

ELECTRIC VEHICLES

Will Barnard

Pam Becker

Troy “Hugin” Noble

Linda Sonne

Jonathan Weiss

Christian Wiest

Ted Yu

Coming soon to your everyday life!


Agenda

Agenda

  • EV Overview

  • EV Value Proposition

  • Bayesian Network Overview

  • Results and Sensitivity

  • Limitations of Model

  • Recommendations


What are ev s

What are EV’s?


Why should people like driving an ev

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

But are they safe?


Where can i charge how long will it take how far can i go

Where can I charge?How long will it take?How far can I go?


What is the cost

What is the cost?

  • Vehicle

    • Purchase

    • Lease

    • Subsidies

  • Ownership

    • Battery Replacement

    • Wear and Tear

  • Refueling


Consumer sensitivity

Consumer Sensitivity

Minimum Efficient Scale: 60% AcceptancePrice: $1,000 PremiumRange: 100 miles


Electric vehicles

Stakeholders


Bayesian network

Bayesian Network:

Problem Statement:

Determine the probability of success of EV’s for an existing car manufacturer.


Network weights

Network Weights

0.35

0.20

0.20

0.15


Results and sensitivity analysis

Results and Sensitivity Analysis

  • Results:

    Probability (Supply = High) = 54.79%

  • Sensitivity:

    • 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

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

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


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