基于主成分分析(PCA)的柴油车驾驶参数与排放优化

G. M. Hasan Shahariar, T. Bodisco, T. C. Van, N. Surawski, M. Sajjad, A. Kabir, Z. Ristovski, Richard J. Brown
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引用次数: 3

摘要

轻型柴油车是造成城市空气污染的主要原因。基于实验室的标准驾驶测试周期没有考虑外部驾驶因素,与实际驾驶排放(RDE)测量相比,外部驾驶因素对车辆排放的影响很大。与标准方法相比,这导致通过RDE测试获得的排放水平更高。在目前的研究中,使用便携式排放测量系统(PEMS)在布里斯班城市交通中进行了RDE测量活动。30多名具有丰富驾驶经验的司机乘坐现代iLoad货车,在定制的测试路线上参加了测试。每趟行程记录RDEs和驾驶参数。采用主成分分析(PCA)研究了驾驶动力学与车辆排放之间的关系。此外,不同的行程、驾驶时间和驾驶经验对驾驶行为和排放的影响。路线熟悉度、交通密度和驾驶经验对驾驶行为和排放有很大影响。驾驶员对变化的交通、未知的路线和车辆的反应在不同的驾驶员之间有很大的不同,这导致了大量的瞬时事件(频繁的加速和减速)。瞬态事件在城市驾驶中非常常见,与车辆排放有很强的相关性。
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Optimisation of driving-parameters and emissions of a diesel-vehicle using principal component analysis (PCA)
Light-duty diesel vehicles contribute significantly to urban air pollution. Laboratory-based standard driving test cycles do not take into account external driving factors, which greatly impact the vehicle emissions compared to the real-world driving emission (RDE) measurements. This results in higher emission levels obtained by RDE tests, compared to the standard approaches. In the current study, an RDE measurement campaign has been conducted in Brisbane city traffic using a portable emission measurement system (PEMS). Thirty drivers with a wide variety of driving experiences participated using a Hyundai iLoad van in a custom test route. RDEs and driving parameters were recorded during each trip. Principal component analysis (PCA) was applied to investigate the relationship between driving dynamics and vehicle emissions. Also, the impact of different trips, driving time, and driving experience on driving behaviour and emissions. Route familiarity, traffic density, and driving experience have a strong impact on driving behaviour and emissions. The driver's response to changing traffic, unknown routes, and vehicles significantly vary among different drivers which results in a high volume of transient events (frequent acceleration and deceleration). Transient events are very common in city driving which has a strong correlation to vehicle emissions.
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