The environmental friendliness of a vehicle is determined by the level of harmful compound emissions. Measurements of vehicle emissions in real-world driving conditions using a system of mobile PEMS analyzers indicate the random nature of harmful compound concentration profiles. The article adopts the research hypothesis that despite the immense complexity and diversity of the conditions under which the experiment was conducted, it is possible to find a statistical similarity between the random emission profiles of CO, CO2, HC, and NOx pollutant variability. The ANOVA analysis of variance method was used to verify the adopted research hypothesis.INTRODUCTION
The environmental friendliness of a vehicle is determined by the level of harmful compound emissions, which are subject to assessment according to exhaust toxicity standards. For motor vehicles, emission measurements are performed in type-approval exhaust toxicity tests conducted on a chassis dynamometer (passenger cars) or an engine dynamometer (truck engines). Road emissions of exhaust components are determined as an averaged value from the entire driving test. In the European Union, current exhaust emission limits are designated as Euro V [1], which concern carbon monoxide, hydrocarbons, nitrogen oxides, particulate matter, and indirectly, fuel consumption measured by carbon dioxide emissions.
To assess emissions in real-world operating conditions (after a specific mileage), mobile PEMS (Portable Emissions Measurement System) [2] devices are used, which are a system of modern analyzers simultaneously recording engine and vehicle parameters via the on-board diagnostics system.
Road tests belong to the category of studies where non-repeatability is a source of information in the process of modeling the phenomena under investigation. The non-repeatability of test results during road tests is a result of the fact that [2, 4]:
• actual emissions in individual tests are different – emission values of pollutants from the same car or engine measured under similar conditions (ambient atmospheric conditions, fuel) measured without measurement errors differ from each other, (…)
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Source: Logistyka Magazine 4/2011