Abstract: Carbon emissions from heavy-duty commercial vehicles account for approximately 5.2% of the total carbon emissions of the whole society in China. However, the heavy-duty commercial vehicle market and its operating conditions are complex, and the powertrain matching is not precise enough, which affects the energy consumption performance. Based on the characteristics of segmented markets and big data of operating vehicles, this paper conducts a study on the powertrain of long-haul logistics tractors. By adopting methods such as classification and clustering, it processes the big data of vehicle driving, extracts the typical altitude-vehicle speed spectrum of segmented markets, clarifies the core concerns of segmented markets, and explores and determines optimization schemes according to the typical altitude-vehicle speed spectrum and core concerns. The results show that the powertrain of "large displacement, low speed, high torque engine" with "large head gear, variable differential multi-speed transmission" can reduce the energy consumption by 2%～5% and improve the power performance by 2%～10% in the long-distance logistics traction market. This study provides a theoretical basis and data support for further energy conservation and carbon reduction of heavy-duty commercial vehicles.

Key words: segmented market; big data; typical altitude-vehicle speed spectrum; energy conservation and emission reduction; power performance; fuel economy

摘要： 重型商用车辆碳排放约占我国全社会碳排放总量的 5.2%，而重型商用车市场及工况复 杂，动力总成匹配不够精准，影响能耗表现。文章基于细分市场特点及运营车辆大数据，对 长途物流牵引车动力总成进行研究，通过分类聚类等方法处理车辆行驶大数据、提取细分市 场典型海拔-车速谱、明确细分市场核心关注点，根据典型海拔-车速谱及核心关注点探索确定 优化方案。数据结果表明，“大排量低转速大扭矩发动机”搭配“大头挡变级差多挡位变速器”的 动力总成方案在长途物流牵引市场实现 2%～5%的能耗降低与 2%～10%的动力性能提升。该 研究为重型商用车辆进一步节能减碳提供了理论基础及数据支持。

关键词: 细分市场；大数据；典型海拔-车速谱；节能减排；动力性；经济性