Suarez Jaime, Makridis Michail, Anesiadou Aikaterini, Komnos Dimitrios, Ciuffo Biagio, Fontaras Georgios
European Commission, Joint Research Centre (JRC), Ispra, Italy.
ETH Zürich, Institute for Transport Planning and Systems (IVT), Zürich, Switzerland.
Transp Res D Transp Environ. 2022 Jun;107:103282. doi: 10.1016/j.trd.2022.103282.
The study proposes a methodology for quantifying the impact of real-world heterogeneous driving behavior on vehicle energy consumption, linking instantaneous acceleration heterogeneity and CO emissions. Data recorded from 20 different drivers under real driving are benchmarked against the Worldwide Harmonized Light Vehicle Test Cycle (WLTC), first by correlating the speed cycle with individual driver behavior and then by quantifying the CO emissions and consumption. The vehicle-Independent Driving Style metric (IDS) is used to quantify acceleration dynamicity, introducing driving style stochasticity by means of probability distribution functions. Results show that the WLTC cycle assumes a relatively smooth acceleration style compared to the observed ones. The method successfully associates acceleration dynamicity to CO emissions. We observe a 5% difference in the CO emissions between the most favourable and the least favourable case. The intra-driver variance reached 3%, while the inter-driver variance is below 2%. The approach can be used for quantifying the driving style induced emissions divergence.
该研究提出了一种方法，用于量化现实世界中异质驾驶行为对车辆能源消耗的影响，将瞬时加速度异质性与一氧化碳排放联系起来。在实际驾驶中记录的20名不同驾驶员的数据，首先通过将速度循环与个体驾驶员行为进行关联，然后通过量化一氧化碳排放和消耗，与全球统一轻型车辆测试循环（WLTC）进行对比。使用与车辆无关的驾驶风格指标（IDS）来量化加速度动态性，并通过概率分布函数引入驾驶风格的随机性。结果表明，与观察到的驾驶风格相比，WLTC循环假设了一种相对平稳的加速风格。该方法成功地将加速度动态性与一氧化碳排放联系起来。我们观察到最有利情况和最不利情况之间的一氧化碳排放有5%的差异。驾驶员内部差异达到3%，而驾驶员之间的差异低于2%。该方法可用于量化驾驶风格引起的排放差异。
