摘 要：为更准确识别车辆驾驶环境并优化能耗，本文基于实际行驶工况数据，选取平均车速、停车时间比、加速时间比及减速时间比等特征参数，并采用模糊C均值聚类方法对行驶工况进行分类。在此基础上，结合车辆工况、驾驶模式和预设规则库等多重因素，构建了一种基于规则的驾驶模式自适应切换策略。该策略能够根据实时驾驶环境自动选择相匹配的驾驶模式，从而提升整车对复杂行驶条件的适应性与能耗经济性。
关键词：纯电动客车；工况聚类识别；驾驶模式；自适应切换
中图分类号：U469.1 文献标志码：A DOI：10.15917/j.cnki.1006-3331.2026.01.004
Research on Adaptive Switching Control of Pure Electric Bus Driving Mode Based on Condition Clustering and Recognition
LI Wenhao,HUANG Yupeng,YANG Chuankai,CHEN Zhenguo,WU Hongting
Abstract: To cluster the driving conditions and identify the current driving environment,this paper selects characteristic parameters such as average speed,stop time ratio,acceleration time ratio,and deceleration time ratio,from real-world driving data and applies the fuzzy C-means clustering method for analysis.Building on the clustering results,a rule-based driving mode switching strategy is developed by integrating vehicle status,driving environment,and predefined rule set to achieve adaptive switching.The proposed strategy automatically selects the matching driving mode based on real-time conditions,thereby enhancing the vehicle's adaptability to varying driving scenarios and improving its overall energy economy.
Key words: pure electric bus; condition clustering and recognition; driving mode; adaptive switching
