主办：陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊：1976年
汽车实用技术

汽车实用技术 ›› 2026, Vol. 51 ›› Issue (2): 1-5,26.DOI: 10.16638/j.cnki.1671-7988.2026.002.001

• 新能源汽车 •    

基于新能源汽车用户大数据的行驶工况研究

武振 1，霍涛 2，王均天 3，邱慕逵 3   

  1. 1.中汽研汽车检验中心（天津）有限公司；2.工业和信息化部装备工业发展中心 ；3.上汽通用五菱汽车股份有限公司
  • 发布日期:2026-01-26
  • 通讯作者: 武振
  • 作者简介:武振（1994－），男，工程师，研究方向为新能源汽车测试评价
  • 基金资助:
    广西重大专项计划“新能源汽车用户大数据场景构建技术研究与应用平台建设”（桂科 AA23062084）

Research on Driving Conditions Based on Big Data of New Energy Vehicle Users

WU Zhen1 , HUO Tao2 , WANG Juntian3 , QIU Mukui3   

  1. 1.CATARC Automotive Test Center (Tianjin) Company Limited; 2.Ministry of Industry and Information Technology Equipment Industry Development Center; 3.SAIC GM Wuling Automobile Company Limited
  • Published:2026-01-26
  • Contact: WU Zhen

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摘要： 随着新能源汽车用户群体的持续增加，文章基于某新能源汽车用户的车联网大数据， 首先对新能源汽车用户的行驶工况特征进行了分析研究，从用户使用的道路类型、行驶里程、 行驶车速、载重分布进行了用户画像的构建和分析。同时，基于用户画像进行了用户工况的 构建，通过 2024 年 5 月的假期和非假期的大数据对以上维度分别进行加权计算，得到了各维 度下的新能源汽车用户工况总体加权分布，道路类型划分为了 7 类、车速划分为了 24 个区间、 载重分布划分为了 3 类，并分别计算得到了占比数据。最后，提出了用户画像和用户工况的 构建在用户道路数据采集的应用，如用户道路载荷谱数据采集的路线规划。

关键词: 新能源汽车；大数据；用户画像；行驶工况；数据采集

Abstract: With the continuous increase of the user group of new energy vehicles, based on the big data of the internet of vehicles of a certain new energy vehicle user, this paper first analyzes and studies the driving condition characteristics of new energy vehicle users. It constructs and analyzes user portraits from the aspects of road types used by users, driving mileage, driving speed, and load distribution. Meanwhile, based on the user profile, the user working conditions are constructed. Through the big data of the holiday and non-holiday period in May 2024, the above dimensions are weighted and calculated respectively, obtaining the overall weighted distribution of the user working conditions of new energy vehicles under each dimension. The road types are classified into 7 categories, the vehicle speeds into 24 intervals, and the load distribution into 3 categories. And the proportion data are calculated respectively. Finally, the application of user profiling and user working condition construction in user road data collection is proposed, such as route planning for user road load spectrum data collection.

Key words: new energy vehicles; big data; user profiling; driving conditions; data collection