基于实车行驶工况的电动公交运营期碳足迹测算

针对电动公交车运营期碳足迹难以监测的难题，本文设计了一种以实车行驶工况为基础的电动公交车碳排放折算量估计方法。以西安市主城区的609路和新建城区的362路公交车为研究对象，基于实车行驶轨迹数据提出一种面向城市电动公交运营线路的本地化驾驶工况构建方案。首先，引入T-SNE非线性机器学习算法进行数据降维，使用Birch聚类方法进行分类；然后，根据相似度最高原则和各类别比例关系构建两条线路的电动公交车运行工况。在Cruise仿真环境进行百公里耗电量计算，并折算得到碳排放量。结果表明：609路和362路同车型电动公交车百公里能耗分别为121.71 kW ⋅ h 和144.46 kW ⋅ h ，差异较为明显，证明了分线路进行驾驶工况构建的必要性；基于本文提出的估计方法计算了两条公交线电动公交车组在2019年11月的碳足迹，分别为114.099 t和117.863 t。提出的电动公交运营期碳足迹测算方法有助于推行城市交通碳排放监测与管理。

Calculation of Carbon Footprint of Electric Bus Operation Based on Real World Driving Cycles

To monitor the carbon footprint of electric bus operations, this paper proposes a method to estimate the converted carbon emissions of electric buses based on the actual driving conditions. Taking the bus route 609 operating in the urban area of Xi'an City and the bus route 362 in the new built urban area as examples, based on real world driving data, a developmentscheme of localized driving cycles for urban electric bus operation lines is proposed. The T- distributed stochastic neighbor embedding (T- SNE) method is used for data dimensionality reduction. The Birch clustering method is used for classification, and then the driving cycles of the two study bus routes were constructed based on the principle of highest similarity and the ratio of each speed interval. The carbon emission is obtained through the conversion formula based on the power consumption calculated in cruise simulation environment. The results indicate that the electric bus routes 609 and 362 show obvious different energy consumption per 100 kilometers, which are respectively 121.71 kilowatt hourand 144.46 kilowatt hour. The result proves the necessity of constructing driving cycles for different bus routes. The carbon footprints of the routes 609 and 362 in November 2019 were also calculated based on the proposed method, which are respectively 114.099 ton and 117.863 ton. The proposed carbon footprint calculation method for electric bus is helpful for urban transportation carbon emission monitoring and management.