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Development of a driving cycle for Istanbul bus rapid transit based on real-world data using stratified sampling method

机译:使用分层采样方法,基于实际数据,为伊斯坦布尔公交快速公交开发一个行驶周期

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摘要

Environmental as well as financial issues forces to develop clean, efficient, and sustainable vehicles which constitutes an integral part of our daily life for urban transportation. Nevertheless, exhaust emissions of conventional internal combustion engine vehicles are the major source of global warming lead greenhouse effect. One solution for this issue is hybridization/electrification of the vehicles.One of the most important tools which can help to test performances of technical solutions systematically is driving cycles representing real driving conditions for vehicle emissions testing and estimation. When the history of the driving cycles was reviewed, it can be seen that there were big changes from constructing synthetically to real world cycles and from emission-focused cycles to emission, pollution and fuel consumption focused cycles. And now, a new application such as hybridization and/or electrification has been added to driving cycles.Main aim of this study is to create a practical driving cycle for Bus Rapid Transit (BRT) vehicles. To do this, characteristic driving parameters such as speed, distance, time, acceleration have been determined first. Data acquisition from conventional vehicles running on Istanbul route was performed and then data were analysed. A driving cycle was developed by using Proportional Stratified Sampling (PSS) technique. Comparison between constructed driving cycle and the real-world data show that difference is less than 10%. And so, it can be concluded that proposed driving cycle was acceptable.
机译:环境和财务问题迫使人们开发清洁,高效和可持续的车辆,这些车辆已成为我们城市交通日常生活中不可或缺的一部分。然而,常规内燃机车辆的废气排放是导致全球变暖导致温室效应的主要来源。解决该问题的一种方法是车辆的混合动力/电气化。可以系统地测试技术解决方案性能的最重要工具之一是代表车辆排放测试和估算的实际驾驶条件的驾驶循环。回顾一下驾驶循环的历史,可以发现从合成循环到实际循环以及从以排放为重点的循环到以排放,污染和燃料消耗为重点的循环都发生了巨大变化。如今,混合动力和/或电气化等新应用已添加到驾驶循环中。本研究的主要目的是为公交快速公交(BRT)车辆创建实用的驾驶循环。为此,首先确定了特征驱动参数,例如速度,距离,时间,加速度。进行了从在伊斯坦布尔路线上行驶的常规车辆的数据采集,然后对数据进行了分析。通过使用比例分层采样(PSS)技术开发了一个驾驶循环。实际行驶周期与实际数据之间的比较表明,差异小于10%。因此,可以得出结论,建议的驾驶周期是可以接受的。

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