Determination of exhaust emission characteristics in the RDE test using the Monte Carlo method

• Autorzy: Andrych-Zalewska Monika , Chłopek Zdzisław , Merkisz Jerzy , Pielecha Jacek

Identyfikatory

DOI

10.5604/01.3001.0016.3127

• Języki publikacji: EN

Abstrakty

EN

The article presents a method of determining the characteristics of exhaust emissions and fuel mass consumption in real driving conditions based on a single test using the Monte Carlo method. The exhaust emission characteristics used are the relations between the emissions and the average vehicle speed, and the characteristic of the fuel mass consumption is the dependence of the fuel mass consumption at the average vehicle speed. The results of empirical research of a passenger car with a spark-ignition engine in the RDE test were used. The use of the Monte Carlo method made it possible to select the initial and final moments of averaging the process values, thanks to which it was possible to determine the discrete values of the characteristics for various values of average vehicle speeds. The determined discrete characteristics of the particulate mass and number emissions and fuel mass consumption relative to the average vehicle speed were approximated by polynomial functions of the second and third degree. The determined discrete characteristics, presented as sets of points, were characterized by a relatively small dispersion in relation to their polynomial approximations. The average relative deviation of the points of discrete characteristics from the value of the polynomial was in most cases small – less than 4%, only in the case of the number of particles emitted deviated from this, as the average relative deviation of the measured points from the determined polynomial was nearly 14%. Combined with the results of RDE empirical studies, the Monte Carlo method proved to be an effective method for determining the characteristics of exhaust emissions, measured in real vehicle operating conditions. The main advantage of the proposed method was a significant reduction in the actual workload necessary to carry out the empirical research – where it became possible to determine the characteristics in a large range of vehicle average speed values with just one drive test. Using standard methods of measuring this type of data, it would be necessary to conduct multiple tests, driving at different average vehicle speeds.

Słowa kluczowe

EN

Monte Carlo method; RDE test; combustion engine; pollutant emission

PL

metoda Monte Carlo; RDE; silnik spalinowy; emisja zanieczyszczeń

• Wydawca: Warsaw University of Technology, Faculty of Transport
• Czasopismo: Archives of Transport
• Rocznik: 2023
• Tom: Vol. 66, iss. 2
• Strony: 45--60
• Opis fizyczny: Bibliogr. 24 poz., wykr., wzory

Twórcy

autor

Andrych-Zalewska Monika

• Wroclaw University of Science and Technology, Faculty of Mechanical Engineering, Wroclaw, Poland

• https://orcid.org/0000-0002-7508-5788

autor

Chłopek Zdzisław

• Warsaw University of Technology, Faculty of Automotive and Construction Machinery Engineering, Warsaw, Poland

• https://orcid.org/0000-0003-0866-7689

autor

Merkisz Jerzy

• Poznan University of Technology, Faculty of Civil and Transport Engineering, Poznan, Poland

• https://orcid.org/0000-0002-1389-0503

autor

Pielecha Jacek

• Poznan University of Technology, Faculty of Civil and Transport Engineering, Poznan, Poland

• https://orcid.org/0000-0001-7586-1989

Bibliografia

• [1] André, M., (2004). The ARTEMIS European driving cycles for measuring car pollutant emissions. Sci Total Environ. 1 (334-335), 73- 84. DOI: 10.1016/j.scitotenv.2004.04.070.
• [2] Andrych-Zalewska, M., Chłopek, Z., Merkisz J., Pielecha, J., (2022). Analysis of the operation states of internal combustion engine in the real driving emissions test. Archives of Transport. 61(1), 71-88. DOI: 10.5604/01.3001.0015.8162.1.
• [3] BUWAL (Bundesamt fur Umwelt, Wald und Landschaft), INFRAS AG (Infrastruktur-, Umwelt- und Wirtschaftsberatung). Luftschadstof-femissionen des Strassenverkehrs 1950-2010, BUWAL-Bericht (1995); 255.
• [4] Chłopek, Z., (2009). The cognitive interpretation of the Monte Carlo method for the technical applications. Eksploatacja i Niezawodnosc – Maintenance and Reliability, 3 (43), 38-46.
• [5] COPERT – Computer Programme to Calculate Emissions From Road Transport.
• [6] EEA/EMEP (2019). Emission Inventory Guidebook.
• [7] Giechaskiel, B., et al., (2016). Implementation of Portable Emissions Measurement Systems (PEMS) for the Real-Driving Emissions (RDE) Regulation in Europe. Journal of Visualized Experiments. 4(118), 54753. DOI: 10.3791/54753.
• [8] Giechaskiel, B., Valverde, V., Clairotte, M., (2021) Real Driving Emissions (RDE): 2020 assessment of Portable Emissions Measurement Systems (PEMS) measurement uncertainty. JCR Technical Report.
• [9] Hölz, P., Böhlke, T., Krämer, T., (2019). Determining water mass flow control strategies for a turbocharged SI engine using a two-stage calculation method. Applied Thermal Engineering, 146, 386-395. DOI: 10.1016/2018.09.133.
• [10] Huertas, J., Quirama, L., Giraldo, M. Díaz, J., (2019). Comparison of three methods for constructing real driving cycles. Energies. 12(4). DOI: 10.3390/12040665.
• [11] Laskowski, P., et al, (2019). Vehicle hydrocarbons’ emission characteristics determined using the Monte Carlo Method. Environmental Modeling and Assessment. 24(3) 311-318. DOI: 10.1007/s10666-018-9640-4.
• [12] Merkisz, J., Bielaczyc, P., Pielecha, J., Woodburn, J., (2019). RDE testing of passenger cars: the effect of the cold start on the emissions results. SAE Technical Paper. DOI: 10.4271/2019-01-0747.
• [13] Merkisz, J., et al., (2020). A comparison of tail pipe gaseous emissions from the RDE and WLTP Test Procedures on a Hybrid Passenger Car. SAE Technical Paper. DOI: 10.4271/2020-01-2217.
• [14] Metropolis, N., Ulam, S., (1949). The Monte Carlo Method. Journal of the American Statistical Association, 44 (247), 335-341. DOI: 10.2307/2280232.
• [15] Mourat, K., Eckstein, C., Koch, T., (2021). A stochastic design optimization methodology to reduce emission spread in combustion engines. Automotive and Engine Technology, 6(1-2).
• [16] PEMS Testing (2020). Portable Emissions Measurement Systems (horiba.com).
• [17] Pielecha, J., Kurtyka, K., (2019). The evaluation of exhaust emission in RDE tests including dynamic driving conditions. Transportation Research Procedia, 40, 338-345. DOI: 10.1016/2019.07.050.
• [18] Probst, D., et al., (2019). Evaluating optimization strategies for engine simulations using machine learning emulators. Journal of Engineering for Gas Turbines and Power, 141(9).
• [19] Savitzky, A., Golay, M. J. E., (1964). Smoothing and differentiation of data by simplified least squares procedures. Analytical Chemistry, 36(8), 1627-1639. DOI: 10.1021/60214a047. [20] Semtech-DS on board vehicle emissions analyzer (2010). User manual. Document: 9510- 086, Revision: 2.01.
• [21] Sun, S., Ertz, M., (2020). Life cycle assessment and Monte Carlo simulation to evaluate the environmental impact of promoting LNG vehicles. MethodsX. 7, 101046. DOI: 10.1016/2020.101046.
• [22] TSI 3090 EEPS™ (Engine Exhaust Particle Sizer™). User manual. 2008.
• [23] Woodburn, J., et al., (2021). Exhaust emissions from two euro 6d-compliant plug-in hybrid vehicles: laboratory and on-road testing. SAE Technical Paper. 2021-01-0605, DOI: 10.4271/2021-01-0605.
• [24] Zhang, J., Tang, H., Chen, M., (2021). Robust design of an adaptive cycle engine performance under component performance uncertainty. Aerospace Science and Technology, 113.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)