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A statistical operating cycle description for prediction of road vehicles' energy consumption

机译:统计运行周期描述,用于预测公路车辆的能耗

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摘要

We propose a novel statistical description of the physical properties of road transport operations by using stochastic models arranged in a hierarchical structure. The description includes speed signs, stops, speed bumps, curvature, topography, road roughness and ground type, with a road type introduced at the top of the hierarchy to group characteristics that are often connected. Methods are described how to generate data on a form (the operating cycle format) that can be used in dynamic simulations to estimate energy usage and CO2 emissions. To showcase the behaviour of the description, two examples are presented using a modular vehicle model for a heavy-duty truck: a sensitivity study on impacts from changes in the environment, and a comparison study on a real goods transport operation with respect to energy usage. It is found that the stop intensity and topography amplitude have the greatest impact in the sensitivity study (8.3% and 9.5% respectively), and the comparison study implies that the statistical description is capable of capturing properties of the road that are significant for vehicular energy usage. Moreover, it is discussed how the statistical description can be used in a vehicle design process, and how the mean CO2 emissions and its variation can be estimated for a vehicle specification.
机译:我们通过使用以分层结构排列的随机模型,提出了关于公路运输运营的物理属性的新颖统计描述。描述包括速度标志,停车站,减速带,曲率,地形,道路崎and度和地面类型,并在层次结构的顶部引入了道路类型,以对经常连接的特征进行分组。描述了如何在表格(操作周期格式)上生成数据的方法,该表格可用于动态仿真中以估算能源使用量和CO2排放量。为了展示描述的行为,使用重型卡车的模块化车辆模型展示了两个示例:对环境变化影响的敏感性研究,以及关于能源使用的实际货物运输操作的比较研究。结果发现,在敏感度研究中,停车强度和地形振幅影响最大(分别为8.3%和9.5%),而比较研究表明,统计描述能够捕获对车辆能量有重要意义的道路特性。用法。此外,还讨论了如何在车辆设计过程中使用统计描述,以及如何为车辆规格估算平均CO2排放量及其变化。

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