Migrating towards Using Electric Vehicles in Fleets – Proposed Methods for Demand Estimation and Fleet Design

Carsharing and electric vehicles have emerged as sustainable transportation alternatives to mitigate transportation, environmental, and social issues in cities. This dissertation combines three correlated topics: carsharing feasibility, electric vehicle carsharing fleet optimization, and efficient fleet management. First, the potential demand for electric vehicle carsharing in Beijing is estimated using data from a survey conducted the summer of 2013 in Beijing. This utilizes statistical analysis method, binary logit regression. Secondly, a model was developed to estimate carsharing mode split by the function of utilization and appropriate carsharing fleet size was simulated under three different fleet types: an EV fleet with level 2 chargers, an EV fleet with level 3 chargers, and a gasoline vehicle fleet. This study also performs an economic analysis to determine the payback period for recovering the initial EV charging infrastructure costs. Finally, this study develops a fleet size and composition optimization model with cost constraints for the University of Tennessee, Knoxville motor pool fleet. This will help the fleet manage efficiently with minimum total costs and greater demand satisfaction. This dissertation can help guide future sustainable transportation planning and policy