Identification of Usage Types for New Energy Vehicles Based on Big Data Analytics

Accurately determining the true usage types of new energy vehicles (NEVs) is crucial for insurance pricing and second-hand market valuation as their use grows. Effective decision-making is hampered by discrepancies between registered and actual use. In order to extract multi-dimensional behavioral indicators, this study suggests a big data-driven framework that slices driving and charging data. A classification model for usage type identification is trained using these. With a 93 % accuracy rate in differentiating between private and taxi-operated vehicles, the method offers useful assistance for regulatory and insurance applications.