Non-regulatory parameters effect on consumption and emissions from a diesel-powered van over the WLTC

Zachiotis, Alexandros T.; Giakoumis, Evangelos G.

doi:10.1016/j.trd.2019.07.019

Cited by 12 publications

(7 citation statements)

References 25 publications

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“…The differences in the courses of curves from Figure 12 have also occurred during vehicle acceleration. Such differences can be noticed in a common road driving, even though higher differences may be caused, for instance by the distance and speed of wind, the road rising/falling gradient and so on [50].…”

Section: Discussionmentioning

confidence: 99%

Air Filter and Selected Vehicle Characteristics

2020

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While a vehicle is driving, the air filter is gradually being clogged. Thus, there is a condition for air mass delivered into the engine’s cylinders to be reduced. It can further degrade the vehicle’s ability to accelerate and, therefore, have an impact on road driving safety, or it can eventually make a vehicle performance worse or cause a change in the exhaust gas composition. The article pays attention to the impact of clogged air filter on selected vehicle characteristics including a vehicle’s dynamic features, fuel consumption and composition of the exhaust gases. The measurements have been performed under laboratory conditions. For higher result objectivity, the measurements have been done under some extreme conditions as well, with both the air filter fully clogged and forced air induction. The importance of the article lies in quantification of the impact of clogged air filter on selected vehicle features. The results from this article show a relatively low impact of air filter on the features studied. The biggest differences were measured under extreme conditions when the air filter had been almost fully clogged, or the air had been delivered into the engine under pressure.

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Section: Discussionmentioning

confidence: 99%

Air Filter and Selected Vehicle Characteristics

2020

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“…For each of the random wind profile WLTC trips, generated based on the methodology described above, instantaneous emissions from a diesel-powered, turbocharged, lightcommercial vehicle were calculated with the use of an integrated engine and vehicle model. This model formed the basis of previous publications of the present research group [30,31] and is briefly discussed here for the sake of completeness.…”

Section: Experimental Investigation and Engine Modelingmentioning

confidence: 99%

“…The rolling resistance coefficient f r was calculated on a second-by-second basis using a detailed mass-spring and damper model to account for tire hysteretic behavior, which is the biggest contributor to rolling resistance losses [49,50]. Tire micro-slippage, as well as tire windage losses, were also considered in the estimation of the rolling resistance coefficient [31].…”

Section: Integrated Engine and Vehicle Modelmentioning

confidence: 99%

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Monte Carlo Simulation Methodology to Assess the Impact of Ambient Wind on Emissions from a Light-Commercial Vehicle Running on the Worldwide-Harmonized Light-Duty Vehicles Test Cycle (WLTC)

Zachiotis

Giakoumis

2021

Energies

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A Monte Carlo simulation methodology is suggested in order to assess the impact of ambient wind on a vehicle’s performance and emissions. A large number of random wind profiles is generated by implementing the Weibull and uniform statistical distributions for wind speed and direction, respectively. Wind speed data are drawn from eight cities across Europe. The vehicle considered is a diesel-powered, turbocharged, light-commercial vehicle and the baseline trip is the worldwide harmonized light-duty vehicles WLTC cycle. A detailed engine-mapping approach is used as the basis for the results, complemented with experimentally derived correction coefficients to account for engine transients. The properties of interest are (engine-out) NO and soot emissions, as well as fuel and energy consumption and CO2 emissions. Results from this study show that there is an aggregate increase in all properties, vis-à-vis the reference case (i.e., zero wind), if ambient wind is to be accounted for in road load calculation. Mean wind speeds for the different sites examined range from 14.6 km/h to 24.2 km/h. The average increase in the properties studied, across all sites, ranges from 0.22% up to 2.52% depending on the trip and the property (CO2, soot, NO, energy consumption) examined. Based on individual trip assessment, it was found that especially at high vehicle speeds where wind drag becomes the major road load force, CO2 emissions may increase by 28%, NO emissions by 22%, and soot emissions by 13% in the presence of strong headwinds. Moreover, it is demonstrated that the adverse effect of headwinds far exceeds the positive effect of tailwinds, thus explaining the overall increase in fuel/energy consumption as well as emissions, while also highlighting the shortcomings of the current certification procedure, which neglects ambient wind effects.

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“…The conditions for dynamometric testing and vehicle loading are based on the strict guidelines of the WLTP test procedure including several Worldwide Harmonized Light-Duty Vehicles Test Cycles (WLTC) [63,64]. These cycles are applicable to vehicle categories with different power-to-weight ratios (unladen weight) [65,66].…”

Section: Introductionmentioning

confidence: 99%

A Computer Tool for Modelling CO2 Emissions in Driving Cycles for Spark Ignition Engines Powered by Biofuels

Tucki¹

2021

Energies

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A driving cycle is a record intended to reflect the regular use of a given type of vehicle, presented as a speed profile recorded over a certain period of time. It is used for the assessment of engine pollutant emissions, fuel consumption analysis and environmental certification procedures. Different driving cycles are used, depending on the region of the world. In addition, drive cycles are used by car manufacturers to optimize vehicle drivelines. The basis of the work presented in the manuscript was a developed computer tool using tests on the Toyota Camry LE 2018 chassis dynamometer, the results of the optimization process of neural network structures and the properties of fuels and biofuels. As a result of the work of the computer tool, the consumption of petrol 95, ethanol, methanol, DME, CNG, LPG and CO2 emissions for the vehicle in question were analyzed in the following driving tests: Environmental Protection Agency (EPA US06 and EPA USSC03); Supplemental Federal Test Procedure (SFTP); Highway Fuel Economy Driving Schedule (HWFET); Federal Test Procedure (FTP-75–EPA); New European Driving Cycle (NEDC); Random Cycle Low (×05); Random Cycle High (×95); Mobile Air Conditioning Test Procedure (MAC TP); Common Artemis Driving Cycles (CADC–Artemis); Worldwide Harmonized Light-Duty Vehicle Test Procedure (WLTP).

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Non-regulatory parameters effect on consumption and emissions from a diesel-powered van over the WLTC

Cited by 12 publications

References 25 publications

Air Filter and Selected Vehicle Characteristics

Air Filter and Selected Vehicle Characteristics

Monte Carlo Simulation Methodology to Assess the Impact of Ambient Wind on Emissions from a Light-Commercial Vehicle Running on the Worldwide-Harmonized Light-Duty Vehicles Test Cycle (WLTC)

A Computer Tool for Modelling CO2 Emissions in Driving Cycles for Spark Ignition Engines Powered by Biofuels

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