基于大数据的商用车个性化省油策略研究

Research on Personalized Fuel Saving Strategy of Commercial Vehicles Based on Big Data

随着能源成本的日益攀升及环保意识的增强,商用车辆的燃油经济性优化愈加成为行业关注的焦点。本研究旨在运用大数据分析技术结合发动机热效率数据,探索并实现商用车的个性化省油策略。通过集成车载传感器数据、GPS行车轨迹信息等多源数据,构建了一套灵活、动态的商用车个性化节油策略。在多个物流车队中部署的实验结果表明,应用本研究所提出的省油策略,平均可节油5.29%,证实了该策略在实际商用车运营中的可行性和经济性。

With the increasing energy costs and environmental awareness,the optimization of commercial vehicle fuel economy has become the focus of the industry.This study aims to use big data analysis technology combined with engine thermal efficiency data to explore and realize personalized fuel saving strategies for commercial vehicles.By integrating on-board sensor data,GPS track information and other multi-source data,we have built a flexible and dynamic personalized fuel saving strategy for commercial vehicles.The experimental results deployed in many logistics fleets show that the fuel saving strategy proposed in this study can save 5.29%on average.It is proved that the strategy is feasible and economical in the actual operation of commercial vehicles.