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Analysis of fuel consumption and pollutant emissions of regulated and alternative driving cycles based on real-world measurements

机译：根据实际测量结果分析规定和替代行驶周期的燃油消耗和污染物排放

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摘要

Discrepancies between real-world use of vehicles and certification cycles are a known issue. This paper presents an analysis of vehicle fuel consumption and pollutant emissions of the European certification cycle (NEDC) and the proposed worldwide harmonized light vehicles test procedure (WLTP) Class 3 cycle using data collected on-road. Sixteen light duty vehicles equipped with different propulsion technologies (spark-ignition engine, compression-ignition engine, parallel hybrid and full hybrid) were monitored using a portable emission measurement system under real-world driving conditions. The on-road data obtained, combined with the Vehicle Specific Power (VSP) methodology, was used to recreate the dynamic conditions of the NEDC and WLTP Class 3 cycle. Individual vehicle certification values of fuel consumption, CO2, HC and NOx emissions were compared with test cycle estimates based on road measurements. The fuel consumption calculated from on road data is, on average, 23.9% and 16.3% higher than certification values for the recreated NEDC and WLTP Class 3 cycle, respectively. Estimated HC emissions are lower in gasoline and hybrid vehicles than certification values. Diesel vehicles present higher estimated NOx emissions compared to current certification values (322% and 326% higher for NOx and 244% and 247% higher for HC + NOx for NEDC and WLTP Class 3 cycle, respectively). (C) 2016 Elsevier Ltd. All rights reserved.
机译：实际使用车辆和认证周期之间的差异是一个已知问题。本文使用道路上收集的数据，对欧洲认证周期（NEDC）的车辆燃油消耗和污染物排放进行了分析，并提出了拟议的全球统一轻型汽车测试程序（WLTP）3类周期。在实际驾驶条件下，使用便携式排放测量系统对16辆配备了不同推进技术的轻型车辆（火花点火发动机，压缩点火发动机，并联混合动力和全混合动力）进行了监测。所获得的公路数据与车辆特定功率（VSP）方法相结合，可用于重新创建NEDC和WLTP 3类循环的动态条件。将各个车辆的燃料消耗量，CO2，HC和NOx排放的认证值与基于道路测量的测试周期估算值进行比较。根据道路数据计算得出的油耗平均分别比重新创建的NEDC和WLTP 3类循环的认证值高23.9％和16.3％。汽油和混合动力汽车的估计HC排放量低于认证值。与当前的认证值相比，柴油车的NOx估算排放量更高（NEDC和WLTP 3类循环的NOx排放量分别增加322％和326％，HC + NOx的排放量分别增加244％和247％）。 （C）2016 Elsevier Ltd.保留所有权利。

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