United States Department of Transportation
i
Feasibility assessment for battery electric vehicles based on multi-day activity-travel patterns.
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2017-04-11
[PDF-3.73 MB]
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Abstract:A Battery Electric Vehicle (BEV) feasibility considering State Of Charge (SOC) level is
assessed using multiday activity-travel patterns to overcome the limitations of using one-day
activity-travel patterns. Since multi-day activity-travel patterns are not readily available,
we generate multi-day activity-travel patterns through sampling from readily available
single-day household travel survey data with considerations of day-to-day intrapersonal
variability. One of the key observation we make is that the distribution of interpersonal
variability in single-day travel activity datasets is similar to the distribution of intrapersonal
variability in multi-day datasets. Thus, interpersonal variability observed in cross-sectional
single-day data of a large population can be used to generate the day-to-day intrapersonal
variability. The proposed sampling method is based on activity-travel pattern type
clustering, travel distance and variability distribution to extract such information from single-day
data. Validation and stability tests of the proposed sampling methods are presented.
BEV feasibility assessment results show that our sampling method combined with trivial
method provide better estimation of population wide BEV feasibility than using cross-sectional
data only.
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