Rush to Charge, Dead to Drive: Application of Deadline Rush Model to Electric Vehicle User's Charging Behavior.

Objective: This work aims to estimate the portion of electric vehicle (EV) users who exhibit procrastination-like behavior, almost equivalent to an "empty" battery, before they decide to charge their vehicles.

Background: There is a human tendency to procrastinate when a deadline approaches. Human behavior in the presence of deadlines has been studied in different fields to evaluate individuals' performance or organizational efficiency and effectiveness. However, this phenomenon has not been investigated among EV users.

Method: This study explores users' procrastination-like behavior among 69 Rhode Island public charging stations' data representing 70,611 charging events. The Deadline Rush Model is incorporated to model frequent users' charging profiles. To conduct a robust estimation, the Bayesian Mixture Model is implemented.

Results: With the selection of an informative prior, the Bayesian Mixture Model estimated that almost one-third of frequent users procrastinate charging.

Conclusion: The majority of procrastination-like users have small battery sizes. Although procrastination-like users need to charge when they arrive at a location, that might not necessarily be true for a plug-in hybrid; thus, systematically, they can clog the system for other users whose needs are more pressing. Understanding unique and unexplored charging behaviors among EV users is beneficial to EV infrastructure stakeholders in reducing the adoption threshold by providing a reliable and ubiquitous charging network.

Application: The findings identify a different kind of demand on the EV infrastructure than previously modeled and can directly influence future decision-making criteria in terms of planning to optimize to accommodate EV drivers with different charging behaviors.