The article deals with the study of exhaust emissions from a combustion engine in the Real Driving Emission (RDE) test. These tests are a simulation of real conditions of use of motor vehicles. Nowadays, RDE tests are mandatory for Light Duty Vehicle (LDV) and Heavy Duty Vehicle (HDV) vehicles and in the future, restrictive standard. Euro 7, which combines stricter limits with a comprehensive RDE test cycle, is becoming a challenge for current vehicle engineering. The paper presents the results of pollutant emission tests from a passenger car (PC). In the tests of LDV in the RDE test, the results of which are analyzed in the article, the Portable Emissions Measurement System (PEMS) mobile exhaust emission testing system was used. The processes describing the operating states of the vehicle and the combustion engine, as well as the processes of exhaust emission intensity and the intensity of the number of particulate (PN), were examined. The correlation between the considered processes was investigated. The emission of carbon monoxide, hydrocarbons, nitrogen oxides, particulate and carbon dioxide as well as the road PN were examined. The zero-dimensional statistical characteristics of the examined processes were also determined. The probability density and power spectral density of the processes were established. A great diversity was found in the properties of the process distributions, as well as in the dynamic properties of the processes. In the summary of the analysis of the results of the car speed process, the operating states of the combustion engine and the processes of exhaust emission intensity and the process of the intensity of PN in the RDE test, conclusions were formulated regarding, among others, course of the intensity of these compounds, correlation of the processes of pollution emission intensity and the intensity of the PN with the process of car speed, distribution of processes.


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    Title :

    Analysis of exhaust emission processes during the Real Driving Emissions test


    Contributors:


    Publication date :

    2023




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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