Two methods of estimating long-distance driving to understand range restrictions on EV use

Abstract

The distances travelled by individual cars vary strongly from day to day. This is problematic for electric vehicles since they cannot be used for journeys longer than the all-electric range. At present, long-distance travel is rarely covered by household travel surveys and little is known about the frequency of long-distance car travel on an individual car basis. Here, two methods are compared that estimate the number of days per year with a driving distance larger than a given threshold: a simulation method and a probabilistic method. The simulation method combines a national household travel survey, a car-use survey and a long-distance travel survey and simulates one year of car driving; the resolution of results is car trips over a full year. The probabilistic method uses statistical distribution to estimate the number of days per year with long-distance travel. Both methods are tested on a representative one-week sample of the German Mobility Panel with travel data from over 6000 cars. Our results show that both methods produce similar aggregated results for the distribution of days with long-distance car travel, the Maximum mileages, and average long-distance travel frequencies amongst user groups. However, the two methods differ on the level of individual cars. Our findings indicate that long-distance travel behaviour can be estimated on an aggregated level without long observation period data. Both methods can be directly applied to the limited range of electric vehicles and the need for adaptation or fast charging.