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Battery Electric Vehicles: Range Optimization and Diversification for the U.S. Drivers...

by Zhenhong Lin
Publication Type
Conference Paper
Publication Date
Conference Name
2012 Transportation Research Board Annual Meeting
Conference Location
Washington, Virginia, United States of America
Conference Sponsor
Transportation Research Board
Conference Date
-

Properly selecting the driving range is critical for accurately predicting the market acceptance and the resulting social benefits of BEVs. Analysis of transportation technology transition could be biased against battery electric vehicles (BEV) and mislead policy making, if BEVs are not represented with optimal ranges. This study proposes a coherent method to optimize the BEV driving range by minimizing the range-related cost, which is formulated as a function of range, battery cost, energy prices, charging frequency, access to backup vehicles, and the cost and refueling hassle of operating the backup vehicle. This method is implemented with a sample of 36,664 drivers, representing U.S. new car drivers, based on the 2009 National Household Travel Survey data. Key findings are: 1) Assuming the near term (2015) battery cost at $405/kWh, about 98% of the sampled drivers are predicted to prefer a range below 200 miles, and about 70% below 100 miles. The most popular 20-mile band of range is 57 to77 miles, unsurprisingly encompassing the Leaf’s EPA-certified 73-mile range. With range limited to 4 or 7 discrete options, the majority are predicted to choose a range below 100 miles. 2) Found as a statistically robust rule of thumb, the BEV optimal range is approximately 0.6% of one’s annual driving distance. 3) Reducing battery costs could motivate demand for larger range, but improving public charging may cause the opposite. 4) Using a single range to represent BEVs in analysis could significantly underestimate their competitiveness— e.g. by $3226/vehicle if BEVs are represented with 73-mile range only or by $7404/BEV if with 150-mile range only. Range optimization and diversification into 4 or 7 range options reduce such analytical bias by 78% or 90%, respectively.