Influence of Vehicle Operators and Fuel Grades on Particulate Emissions of an SI Engine in Dynamic Cycles

Guse, Daniel; Roehrich, Henning; Lenz, Martin; Pischinger, Stefan

doi:10.4271/2018-01-0350

Cited by 9 publications

(7 citation statements)

References 7 publications

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“…These small deviations can lead to a completely different trend in the pollutants emitted. 47,49 Especially at long, constant acceleration intensities, a sinusoidal pedal movement of the driver is observed when trying to “shimmy along the line.” For better reproduction, the effect of an automatic, robot-assisted driver 44 must be investigated during an emission test.…”

Section: Validation Of the Methodology By Implementation Of The Test mentioning

confidence: 99%

“…The driver/vehicle interaction is significantly influenced by the human individual, which makes modeling very difficult and unreliable. 10,49 Both P eff , avg and DrCE show significant differences between the vehicles with regard to the center of gravity positions of the data point clouds. Since these do not result solely from the respective driving resistance coefficients, it can be concluded that a uniform test cycle cannot be a reliable validation option for all different vehicle types.…”

Section: Development Of a Statistical Evaluation Procedures For Rde Cymentioning

confidence: 96%

“…Since engine power is the link between driving behavior and pollutant emissions, a detailed consideration of this parameter is required. 11,49 Many parameters influence the driver/vehicle/powertrain interaction: driver behavior, noise vibration harshness (NVH) (wind or engine noise), drivability, acceleration behavior, fuel costs, and so on. The driver/vehicle interaction is significantly influenced by the human individual, which makes modeling very difficult and unreliable.…”

Section: Development Of a Statistical Evaluation Procedures For Rde Cymentioning

confidence: 99%

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Statistically supported real driving emission calibration: Using cycle generation to provide vehicle-specific and statistically representative test scenarios for Euro 7

Claßen

Pischinger

Krysmon

et al. 2020

International Journal of Engine Research

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The progression of emission legislation has intensified the efforts of the automotive industry to develop improved exhaust gas after-treatment systems. The requirement to fulfill Euro 6d-TEMP in real-world driving scenarios, the already significant calibration effort for Euro 6d and the Euro 7 emission standards in discussion have significantly increased the work load for calibration engineers and the requirements for testing resources. Many original equipment manufacturers are implementing taskforces in order not to have to discard the planned start of production for their products, and some are even already forced to reduce their product portfolio. This is due to the diverse testing matrix required to cover all possible real driving emissions test scenarios. One big challenge is the extension and possible variation of boundary conditions regarding ambient temperatures, traffic conditions, road gradients and other varying driving resistances. Moreover, the test duration can cause considerable differences in the measured emissions, even if the same route is driven repeatedly. Addressing these challenges makes the application of a dedicated, event-targeted emission calibration mandatory. Since only a few sequences of the time-consuming road tests are relevant for improving the emission calibration, the methodology presented in this article focuses on the exact reproduction of these emission events on an emission chassis dynamometer with the aim of implementing calibratable solutions for these events. This is done using a real driving emission-cycle-generator which creates real driving emission compliant severe test scenarios and which focuses on the statistical relevance related to the typical product specific operation. The underlying generation process accesses a large database with real driving emission measurement results focusing on vehicle- or vehicle-group-specific challenges, using statistical approaches. It will be demonstrated how this procedure reduces test time and how it helps to tackle the substantial real driving emission work-load, while providing a dependable base to achieve real driving emission legislation compliance.

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Section: Validation Of the Methodology By Implementation Of The Test mentioning

confidence: 99%

Section: Development Of a Statistical Evaluation Procedures For Rde Cymentioning

confidence: 96%

Section: Development Of a Statistical Evaluation Procedures For Rde Cymentioning

confidence: 99%

See 1 more Smart Citation

Statistically supported real driving emission calibration: Using cycle generation to provide vehicle-specific and statistically representative test scenarios for Euro 7

Claßen

Pischinger

Krysmon

et al. 2020

International Journal of Engine Research

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“…Due to the season, the tests were carried out with the winter variant of standard fuel (RON 95, MON 85, E 5). Because of the influence of different fuel compositions and the effects of fuel quality on the exhaust emission behavior from GDI engines, 34–36 the composition of the fuel used is briefly described in Table 2 as an extract from a laboratory analysis.…”

Section: Measurement Setupmentioning

confidence: 99%

“…Both measuring systems are comparable in the measurement of the PN in the same measurable particle size range, here from 23 to 562 nm. 34…”

Section: Measurement Setupmentioning

confidence: 99%

A case study on particulate emissions from a gasoline plug-in hybrid electric vehicle during engine warm-up, taking into account start–stop operation

Lenz

Cremer

Guse

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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Concerning the discussions about emissions caused by individual mobility, it is foreseeable that future vehicle concepts will increasingly be based on hybrid powertrains. These systems lead to more complex operating scenarios, which have a significant influence on the resulting emissions of the engine. This work shows a case study and the results in the operation and emission behavior of a plug-in hybrid electric vehicle with a direct injection gasoline engine when operated in an internationally recognized driving cycle. The vehicle’s exhaust aftertreatment system consists of a three-way catalytic converter; a particulate filter is not installed. The emissions are analyzed with a focus on particulate number emissions (from soot), especially during the warm-up phase and the frequent start–stop events (in total, there are 12 internal combustion engine operating phases), which are typical for hybrid vehicles. The results show that approximately 50% of the emitted particulates have a smaller size, 23 nm (a very high number of particulates with a mean size of 10 to 15 nm are present), which are currently not regulated, but are expected to have a high risk of adverse health effects.

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Engine-in-the-Loop – Auswirkung der Echtzeitperformance auf die Abbildungsgüte von Fahrzyklen

Walter¹,

Guse

Klein

et al. 2020

Proceedings

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Influence of Vehicle Operators and Fuel Grades on Particulate Emissions of an SI Engine in Dynamic Cycles

Cited by 9 publications

References 7 publications

Statistically supported real driving emission calibration: Using cycle generation to provide vehicle-specific and statistically representative test scenarios for Euro 7

Statistically supported real driving emission calibration: Using cycle generation to provide vehicle-specific and statistically representative test scenarios for Euro 7

A case study on particulate emissions from a gasoline plug-in hybrid electric vehicle during engine warm-up, taking into account start–stop operation

Engine-in-the-Loop – Auswirkung der Echtzeitperformance auf die Abbildungsgüte von Fahrzyklen

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