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Plug-in Vehicles, Retail Performance and Policy

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Subjects: Dealer Role, Market, Policy, ZE MAP

Improving plug-in vehicle retail experience: Is there a role for policy?

Plug-in Vehicles, Retail Performance and Policy Slides

Subjects: Dealer Role, Market, Policy, ZE MAP

New findings on plug-in vehicle charging decisions

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Subjects: Charging, ZE MAP

Accounting for risk shows plug-in vehicles are a smarter investment

By Gustavo Collantes

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Subjects: ZE MAP

Analytic Tool to Support the Implementation of Electric Vehicle Programs

Published by Andrew Burke, Gustavo O. Collantes, Marshall Miller, Hengbing Zhao

This project developed a lifecycle cost of ownership (LCO) model to support the deployment of plug‐in vehicles (PEV) in California. The model is incorporated into a dynamic analytic tool that can be used to understand questions related to LCO. The model uses information from a variety of sources. Detailed drive cycle data was recorded from various routes in the Sacramento and San Francisco regions. The drive cycle data was input to a dynamic vehicle model, Advisor, which calculated fuel economy values (both electric Wh/mi and gasoline gallons/mi) for the various drive cycles. The fuel economy outputs were then input to the LCO model along with relevant parameters such as fuel prices, vehicle cost incentives, costs for insurance, parking, and maintenance. The fuel and electricity prices were stochastically varied to simulate expected future increases and uncertainties. The output of the model is not a fixed cost but rather a distribution of expected costs that can have significant variation. The model includes results for three vehicle types – vehicles similar to the Nissan Leaf, the GM Volt, and the Chevy Cruze. The Advisor model runs showed that increased accessory loads from heating or cooling can have a large effect on fuel economy and range for vehicles operating in electric mode. The LCO varied up to 15% based on the choice of drive cycle.

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Subjects: Market, Policy, ZE MAP