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

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