【摘要】 为满足新能源汽车用户日益多样化的充电需求，采用潜在类别模型(LCM)构建用户充电行为分类体系，解析充电习惯异质性特征，并提出差异化服务策略。通过新能源私家车主问卷调查，收集充电与出行行为特征、态度潜变量以及社会经济属性数据，根据个体在充电时间、频率、电量及充电站选择等行为习惯上的差异，划分出高度规律型、空间探索型、频率波动型、能量起伏型与随机多变型五种用户类别。针对不同用户类别，进一步分析出行行为、风险规避态度等指标，揭示不同充电习惯与出行特征、心理偏好等因素之间的耦合机制。研究结果可为充电服务定制化设计及充电站运营优化提供理论支持，有助于提升充电设施的使用效能和服务质量，从而推动交通行业向智慧电动化转型。更多还原

【Abstract】 To address the increasingly diversified charging demands of battery electric vehicle (BEV) users,a user classification system was constructed using latent class model (LCM) to analyze heterogeneous charging habit characteristics,and targeted service design strategies were proposed.Through a questionnaire survey from private BEV users,data on charging and travel behavior characteristics,latent attitude variables,and socio-economic attributes were collected.Based on behavioral differences in charging time,frequency,energy consumption,and charging station selection among individuals,five distinct user categories were classified:highly regular users,spatial exploratory users,frequency-fluctuating users,energy-oscillating users,and random-variant users.A comparative analysis across different user groups was conducted by integrating differences in travel behaviors,along with latent variables such as risk attitudes,to reveal the underlying sources and coupling mechanisms of charging habit variations.The findings offer valuable insights for designing customized charging services and planning charging station operations,which can enhance the utilization efficiency and service quality of charging facilities,thereby promoting the smart electrification transformation of the transportation industry.更多还原