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 oneday 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 singleday data.