Behavioral Determinants of Electric Vehicle Battery Degradation: Evidence from Large-Scale Real-world Operations

Electric vehicles (EVs) are central to sustainable transport, yet battery service life remains a limiting factor for cost and adoption. Distinct from traditional laboratory-based simulations that often fail to capture the complexity of field conditions, this study investigates how EV user behavior—including driving style and charging demands—influences capacity using large-scale, real-world operational data from daily EV usage. A data-driven framework is developed to quantify driving and charging behaviors through multidimensional feature extraction at the vehicle level and estimate battery State-of-Health (SOH) trajectories, enabling direct linkage between individual behavior patterns and degradation outcomes. Results reveal substantial heterogeneity in aging rates explicitly driven by diverse user behaviors: under identical urban conditions, vehicles with a radical driving style exhibit approximately 81% faster SOH decline per 20,000 km than those with a moderate style ; regarding charging intensity, in controlled comparison scenarios, increasing fast-charge counts from the baseline interval of 90–120 to the elevated interval of 150–180 is associated with a ~2.1% reduction in median SOH when holding other factors constant ; and similarly, increasing deep charge–discharge events from 160–180 to 220–240 corresponds to an additional ~2.0–2.3% cumulative SOH loss. These findings quantify the behavioral determinants of capacity fade in the field and demonstrate that aggressive driving, frequent fast charging, and deep discharge habits materially accelerate battery degradation. The framework provides actionable evidence for adaptive charging guidance and personalized driving strategies, extending battery longevity and enhancing the sustainability of electric mobility systems.