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The energy and environmental benefits of electric vehicles (EVs) are highly dependent on individual driving patterns. To characterize individual driving patterns in Beijing, a populated megacity in East Asian, GPS-based travel data from 459 private passenger vehicles were gathered covering nearly 17,000 sampling days in 2013–2015. The data were analyzed using a statistical model to produce 0.5 h, 4 h, 8 h and daily individual trip chain distributions, which were used to evaluate customer acceptance for battery electric vehicles (BEVs) based on inconvenience thresholds and to assess the energy consumption for plug-in hybrids (PHEVs). The mean daily distances travelled on weekdays and weekends in Beijing were found to be 44.6 km and 51.4 km respectively. In Beijing the mean habitual travel distance (40.4 km) is modest, the random component of travel distance is lower, and the fraction of habitual travel is …