Influences of Real-World Conditions on In-Use Emission from Heavy-Duty Diesel Engines

Thompson, Gregory; Gibble, John; Clark, Nigel N.; Gautam, Mridul

doi:10.4271/2006-01-3393

Cited by 5 publications

(4 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It should be noted that studies concerning relative emissions of blended and/or additized diesel utilized different petroleum diesel as a baseline and the variability of the baseline petroleum diesel may be the cause of varying results. With typical pump diesel fuels commercially available in the USA, Thompson and co-workers [21] showed a variation of 12 per cent in the NO x , 46 per cent in the PM, 11 per cent in the CO, and 30 per cent in the THC emissions for the same engine and test cycle.…”

Section: Introductionmentioning

confidence: 98%

Neat fuel influence on biodiesel blend emissions

Thompson

Nuszkowski

2009

International Journal of Engine Research

View full text Add to dashboard Cite

The emissions of oxides of nitrogen (NO x ) from biodiesel blended fuels reported in the literature vary from an NO x increase to an NO x decrease relative to the neat petroleum diesel fuel (PDF). To explain these NO x differences, three PDFs with varying fuel properties were admixed with a neat soy-derived biodiesel at 10 per cent and 20 per cent volume ratios and evaluated using a heavy-duty diesel engine exercised over transient and steady-state cycles. The PDFs with 'low' and 'medium' cetane numbers led to a change in combustion phasing when blended with the neat biodiesel, resulting in reduced NO x emissions at low engine power. The B100 blended with the 'high'-cetane-number PDF showed minimal change in combustion phasing and resulted in an NO x increase at all engine loads. The derived peak incylinder gas temperature variation correlated with the brake-specific NO x emissions indicating that the thermal NO x formation responds to the addition of biodiesel. The biodiesel blends had an NO x -particulate matter trade-off, also suggesting a thermal NO x effect. The increase in NO x emissions of the biodiesel blends also had a strong correlation with the level of saturated hydrocarbons at high engine power.

show abstract

Section: Introductionmentioning

confidence: 98%

Neat fuel influence on biodiesel blend emissions

Thompson

Nuszkowski

2009

International Journal of Engine Research

View full text Add to dashboard Cite

show abstract

“…Environmental changes can create variances in emissions nearly identical to those mentioned for fuel [31]. These contributions will weigh heavily as emission limits continue to decrease.…”

Section: In-use Challengesmentioning

confidence: 98%

“…Fuel composition can have very great effects on emissions. NO X creation can vary by as much as 12% depending on fuel characteristics [31] and PM can vary by as much as 50%. CO and HC can also vary by as much as 40% and 17%, respectively.…”

Section: In-use Challengesmentioning

confidence: 99%

Simultaneous evaluation of multiple PEMS using an engine dynamometer emissions test cell

McConnell¹

View full text Add to dashboard Cite

Portable emission measurement systems (PEMS) are taking center stage as in-use testing programs are getting underway. EPA-mandated manufacturer-run in-use testing programs require a PEMS, and currently there is one commercially available and widely used, the SEMTECH-D built by Sensors, Inc. The SEMTECH-D was first unveiled in 2002, and numerous software and hardware upgrades have given way to the SEMTECH-DS. The manufacturer claims this system is fully compatible with all new Code of Federal Regulations (CFR) including part 1065 subpart J (which addresses field testing and PEMS). Yet, while West Virginia University (WVU) was using the SEMTECH-D during the summer of 2005, problems were encountered that prompted further insight into its performance. A ten month study ensued to study SEMTECH-D's behavior compared to an EPA certified engine test cell on the campus of WVU at Morgantown, WV. After multiple test days, exhaust configurations, and comparisons to both the heavy-duty engine dynamometer laboratory (compliant with CFR40 Part 86 Subpart N) at WVU, and another PEMS, the SEMTECH-D was found to consistently exhibit high discrepancies. Over a twenty minute Federal Test Procedure (FTP) transient test the total NO X mass emitted error was as high as 25%, while the CO 2 total mass emitted error was as high as 15% compared to the engine dynamometer laboratory.

show abstract

“…It should also be noted that research conducted by Thompson et al has shown that employing different fuels during heavy duty diesel emissions testing has resulted in variations in CO and hydrocarbon production of 40% and 17%, respectively. The quantity of NOx produced has been shown to vary up to 12% when fuels obtained from different commercial suppliers were used [71].…”

Section: Summary Of Repeatabilitymentioning

confidence: 99%

Development of an Artificial Neural Network to Predict In-Use Engine Emissions

Morris¹

View full text Add to dashboard Cite

A method to predict in-use diesel engine emissions is developed based on engine dynamometer and in-use data acquired at the West Virginia University Center for Alternative Fuels, Engines, and Emissions. (WVU CAFEE). The model accounts for the effects of road grade on generated emissions; a need for this model is evident in literature. Current modeling methods do not account for the effects of road grade, and have been shown to under-predict NOx by as much as 57%. It is determined through present research and a review of relevant literature that an artificial neural network (ANN) was the most applicable modeling method. A modular ANN was developed to predict the heavy duty diesel engine emissions. The two modules were trained independently, the first module was trained with data acquired through inuse testing, and the second module was trained with data acquired via engine dynamometer testing. The first module predicted the engine speed and torque associated with the inputs of road grade and vehicle speed, while the second ANN employed the first ANN's outputs, and predicts the emitted quantities of NOx, CO 2 , HC, and CO. A series of training and verification runs are conducted in order to determine the optimum ANN characteristics. Once the ANN was finalized, it was trained with and employed to predict the emissions associated with a variety of routes. When the ANN was trained with a combination of in-use and engine dynamometer data, the ANN is able to predict NOx emissions associated with that same route within 6% of the measured values. The average difference between the measured and predicted CO 2 values for the same training and verification scenario mentioned above was less than 15%. It was also demonstrated that the ANN was able to predict emissions that are associated with routes that differ from those by which it is trained. When the ANN was trained with in-use data from a specific route, it was able to predict the NOx and CO 2 emissions associated with a different route with percent differences from the measured values of 20% or less.

show abstract

Influences of Real-World Conditions on In-Use Emission from Heavy-Duty Diesel Engines

Cited by 5 publications

References 31 publications

Neat fuel influence on biodiesel blend emissions

Neat fuel influence on biodiesel blend emissions

Simultaneous evaluation of multiple PEMS using an engine dynamometer emissions test cell

Development of an Artificial Neural Network to Predict In-Use Engine Emissions

Contact Info

Product

Resources

About