Assessing EV Load Uncertainty in Rental Car Fleets: Statistical Insights for Effective Charging Infrastructure

This study assesses the uncertainty associated with electric vehicle charging loads in rental car fleets and develops a data-driven framework for estimating energy consumption and charging requirements. Using real-world rental contract data, the study analyzes vehicle usage patterns, pick-up and drop-off times, rental durations, and charging energy demand. Multiple probability distributions were evaluated using the Kolmogorov–Smirnov goodness-of-fit test to identify suitable statistical models, providing practical insights for charging infrastructure planning, load management, and vehicle availability.