Range anxiety of battery electric vehicles: Quantification and determinants using real-world data

Quantifying the range anxiety of battery electric vehicles (BEVs) and identifying its determinants are essential for analyzing the charging and driving behaviors of BEV drivers. However, few studies use real-world data to quantify range anxiety and reveal its determinants directly. Based on the 2024 real-world charging and trip data collected from 438 privately owned BEVs in Tianjin, China, this study utilizes the Weber-Fechner law to quantify range anxiety of BEV for each trip and employs machine learning models to analyze its relationships with trip, travel, charging, vehicle, and individual attributes. The results indicate travel time is the most influential factor affecting range anxiety, expressing a logarithmic relationship characterized by diminishing marginal effects. Frequent BEV usage and moderate charging frequency are associated with lower range anxiety. Female users experience heightened range anxiety under low charging speeds and low SOC conditions. Older users generally exhibit higher range anxiety.