Abstract
Because relatively few plug-in hybrid electric vehicles (PHEVs) have been deployed to date, existing analyses of the effects of PHEVs on gasoline and electricity demand have been based on the travel patterns of conventional vehicles and assumption-driven charging scenarios. A comprehensive analysis of a real-world fleet of 125 instrumented PHEV prototypes deployed in the United States over a 1-year period—likely the first application of a discrete choice model to the empirical analysis of plug-in vehicle charging—is presented. First, the trial is introduced, and the patterns of travel, charging behavior, and observed energy consumption are analyzed. Then, a mixed logit model of the decision to charge at the end of each trip is estimated. Results indicate that charging usually is done after the day's last trip when ending at home and when the next trip will occur in more than 3 h, even though significant heterogeneity exists between drivers. Finally, the performance of this fleet is simulated with different vehicle designs and charging patterns. Results indicate that aggressive opportunistic charging after every trip results in approximately the same fuel savings as increasing the battery size by a factor of five. However, fast charging provides only marginal changes in energy use for the observed use patterns.
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