Development and Initial Use of a Heavy-Duty Diesel Truck Test Schedule for Emissions Characterization

Gautam, Mridul; Clark, Nigel N.; Riddle, Wesley; Nine, Ralph D.; Wayne, W. Scott; Maldonado, Hector; Agrawal, Archana; Carlock, Mark

doi:10.4271/2002-01-1753

Cited by 41 publications

(29 citation statements)

References 5 publications

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“…These trucks were considered to be malfunctioning during the original E-55/59 study, using criteria for PM emissions based on the transient and cruise modes of the heavy heavy-duty diesel truck (HHDDT) schedule. 17,18 It is believed that these trucks had injection malfunctions and that high PM was because of high unburned fuel (organic carbon).…”

Section: Results and Discussion: Translab Datamentioning

confidence: 99%

Idle Emissions from Heavy-Duty Diesel Vehicles: Review and Recent Data

Khan

Clark

Thompson

et al. 2006

Journal of the Air & Waste Management Association

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Heavy-duty diesel vehicle idling consumes fuel and reduces atmospheric quality, but its restriction cannot simply be proscribed, because cab heat or air-conditioning provides essential driver comfort. A comprehensive tailpipe emissions database to describe idling impacts is not yet available. This paper presents a substantial data set that incorporates results from the West Virginia University transient engine test cell, the E-55/59 Study and the Gasoline/Diesel PM Split Study. It covered 75 heavy-duty diesel engines and trucks, which were divided into two groups: vehicles with mechanical fuel injection (MFI) and vehicles with electronic fuel injection (EFI). Idle emissions of CO, hydrocarbon (HC), oxides of nitrogen (NO x ), particulate matter (PM), and carbon dioxide (CO 2 ) have been reported. Idle CO 2 emissions allowed the projection of fuel consumption during idling. Test-to-test variations were observed for repeat idle tests on the same vehicle because of measurement variation, accessory loads, and ambient conditions. Vehicles fitted with EFI, on average, emitted ϳ20 g/hr of CO, 6 g/hr of HC, 86 g/hr of NO x , 1 g/hr of PM, and 4636 g/hr of CO 2 during idle. MFI equipped vehicles emitted ϳ35 g/hr of CO, 23 g/hr of HC, 48 g/hr of NO x , 4 g/hr of PM, and 4484 g/hr of CO 2 , on average, during idle. Vehicles with EFI emitted less idle CO, HC, and PM, which could be attributed to the efficient combustion and superior fuel atomization in EFI systems. Idle NO x , however, increased with EFI, which corresponds with the advancing of timing to improve idle combustion. Fuel injection management did not have any effect on CO 2 and, hence, fuel consumption. Use of air conditioning without increasing engine speed increased idle CO 2 , NO x , PM, HC, and fuel consumption by 25% on average. When the engine speed was elevated from 600 to 1100 revolutions per minute, CO 2 and NO x emissions and fuel consumption increased by Ͼ150%, whereas PM and HC emissions increased by ϳ100% and 70%, respectively. Six Detroit Diesel Corp. (DDC) Series 60 engines in engine test cell were found to emit less CO, NO x , and PM emissions and consumed fuel at only 75% of the level found in the chassis dynamometer data. This is because fan and compressor loads were absent in the engine test cell.

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Section: Results and Discussion: Translab Datamentioning

confidence: 99%

Idle Emissions from Heavy-Duty Diesel Vehicles: Review and Recent Data

Khan

Clark

Thompson

et al. 2006

Journal of the Air & Waste Management Association

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“…It describes the behaviour of vehicle driving under congested conditions with frequent stop-and-go at a very low speed range. Creeping driving period for a heavy duty vehicle can be up to an average length of four minutes with an average speed lower than 5 km/hr (Gautam et al, 2002). Obviously, such low speed and frequently stop-and-go driving behaviour would contribute significantly to emission levels.…”

Section: Downloaded By [] At 04:02 01 October 2014mentioning

confidence: 99%

“…Later, Dai et al (2008) further refined the Markov process approach by using more emissions related variables as well as matching with SAFD and the modal distributions. The Heavy Heavy-Duty Diesel Truck (HHDDT) driving cycle was a sequential combination of sub-cycles developed for each operating mode (Gautam et al, 2002). Recently, Liaw and Dubarry (2007) employed a new approach that comprises fuzzy logic pattern recognition (FL-PR) techniques to perform driving and duty cycle analysis for electric hybrid vehicles.…”

Section: United States Driving Cyclesmentioning

confidence: 99%

“…Obviously, such low speed and frequently stop-and-go driving behaviour would contribute significantly to emission levels. A separate cycle was developed for this particular mode in the HHDDT cycle development study (Gautam et al, 2002). Therefore, it is important to include this mode for driving cycles developed for urban and congested driving environments.…”

Section: Downloaded By [] At 04:02 01 October 2014mentioning

confidence: 99%

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A Framework for Developing Driving Cycles with On‐Road Driving Data

Tong¹,

Hung

2010

Transport Reviews

101

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This paper attempts to propose a framework on driving cycle development based on a thorough review of 101 transient driving cycles. A comparison of the driving cycles highlighted that Asian driving is the slowest but most aggressive while European driving is the fastest and smoothest. Further review of the cycle development methodologies identified three major elements for developing a driving cycle; test route selection, data collection and cycle construction methods. A framework was eventually proposed based on these findings and recommendations from this review. First, traffic activity patterns and quantitative statistics should be considered in determining the test routes. Speed data can be collected by using chase car method, on-board measurement techniques or their hybrid. As for the construction of driving cycle, the matching approach has been more commonly used. It is recommended that the tendency of zero change in acceleration, which has been commonly ignored in the literature, and the application of succession probability at second-by-second level should be further explored. A fifth mode, creeping, is also recommended for modal analysis for characterizing urban congested driving conditions.

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“…The UDDS is a seventeen minute cycle with a peak speed of 60 mph and is representative of the heavy-duty driving in US urban conditions. The development and examination of HHDDT schedule was presented elsewhere [21] …”

Section: Drive Cycles Used For the Chassis Dynamometer Datamentioning

confidence: 99%