Browsing by Author "Dr. H. Christopher Frey, Committee Chair"

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Assessment of On-Board Emissions and Energy Use of Nonroad Construction Vehicles
(2006-11-14) Abolhasani, Saeed; Dr. H. Christopher Frey, Committee Chair; Dr. M. Nagui Rouphail, Committee Member; Dr. Donald Van der vaart, Committee Member
In the past decade, nonroad engine emissions have increasingly become the focus of regulatory actions and air quality improvement strategies. The U.S. Environmental Protection Agency is undertaking an effort to develop a new set of modeling tools for estimation of emissions produced by nonroad vehicles. A critical element of the new models is the use of data gathered using on-board emissions measurement systems. Recent developments in on-board instrumentation enable measurement of vehicle activity and emissions under real- world conditions as opposed to laboratory tests. The primary purpose of this thesis is to develop methodologies for on-board vehicle activity and emissions data collection, screening, and analysis for construction vehicles. The method was applied to field data collection for three excavators. Analysis of on-board data provided insights regarding quantification of variability in vehicle emissions and fuel consumption data. The influence of vehicle activity patterns on the average emission and fuel consumption rates was characterized using engine manifold absolute pressure. A consistent finding is that NO and CO2 emissions are highly correlated to fuel consumption, reflected in an average coefficient of determination of 0.96 between either of these emission rates and fuel consumption rate. Short-term episodes can produce a substantial portion of total emissions. For example, on average, 50% of the total NO emissions were associated with 28% of the time of vehicle operation, during which the average engine speed and manifold absolute pressure were significantly higher than corresponding averages for the total data. A secondary, but equally important, purpose was to demonstrate a conceptual analytical methodology for analyzing on-board emissions data from nonroad construction vehicles and develop conceptual models to predict emissions using on-board data. Several different modeling methods were explored, including stratification of the data into operating modes, supplementing the modal models with ordinary least square regression, and multiple least squares regression. The modal approach offers the advantages of being conceptually the simplest, reducing the influence of autocorrelation in the model, and offering substantial explanatory power. The relationship between predicted mode-specific average emissions and exhaust flow was found to be stable, similar, and consistent for all vehicles. On average, an improvement in coefficient of determination value from 0.85 to 0.93 was estimated for observed versus estimated NOx emissions using combined-regression modal versus simple modal approach. Modal models can be used in a new set of modeling tools to estimate emissions produced by nonroad construction vehicles.
Evaluation of Freight Truck Anti-Idling Strategies for Reduction of Greenhouse Gas Emissions
(2008-08-19) Kuo, Po-Yao; Dr. H. Christopher Frey, Committee Chair
It is important to identify ways to reduce greenhouse gas (GHG) emissions in order to combat climate change. Freight trucks emit 5.5 percent of U.S. GHG emissions and one of key sources is long-haul sleeper cab truck engine idling. Some anti-idling strategies, such as auxiliary power unit (APU) and shore-power (SP), have been developed. The objective of this study is to assess the anti-idling techniques taking into account variability in of real-world; to develop a new methodology for measurement and evaluation of such techniques; and to obtain new data. Anti-idling techniques as well as other strategies are assessed based on literature review. For robust assessment for specific situation, a methodology for quantifying real-world truck stop activities and fuel use and emission rates for the base engine and anti-idling techniques is developed. Quantified data are used to estimate avoided fuel use and emissions. Thirty-three potential best practices for freight trucks are assessed. These practices could lead to 28 percent reduction of GHG emissions from 2003 to 2025. Some practices were estimated to have net cost savings concurrent with substantial GHG emission reductions. Sensitivity analysis was used to assess the effects of variability and uncertainty; for example, for APUs GHG emission reductions could vary from 0 to 5 percent. In order to more accurately assess the impact of APUs and SP, a detailed field study was executed. A new methodology was developed to estimate real-world fuel use and emissions of twenty APU-equipped and SP-compatible trucks, divided equally between single drivers and team drivers. Single drivers had 1,520 hours of rest stops per year, which were comparable to the literature estimates but more than those for team drivers. APUs for single and team drivers accounted for 59 and 25 percent, respectively, of idling hours. For two trucks, APUs accounted for 85 percent of idling hours. Double-dipping, which is simultaneous usage of the base engine and APU and defeats the purpose of the APU, accounted for 0.1 to 29% of idling hours. SP usage was seldom observed. Energy use rates are estimated based on electronic control unit data for truck engines and electrical load measurement for APU and SP. Engine emission factors were measured using a portable emission measurement system. Indirect emission factors from SP are based on utility grid emission factors. Fuel use rates are typically lowest in mild weather and highest in very hot or cold weather. Compared to the base engine, fuel use and CO2 emissions rates for the APU and SP are lower by 36 to 47 and 74 to 92 percent, respectively. Taking into account the actual proportion of idling time for which the APU is used instead of the base engine, the avoided fuel use and CO2 emissions for single and team drivers are 22 and 5 percent, respectively. The projected avoided fuel use and emissions are lower than those from literature sources. The difference is because of relatively low base engine idling fuel use and emissions rates, relatively high APU fuel use and emissions rates, lower idle reduction activity, and double-dipping. Because of low APU utilization rates, 17 of the 20 trucks have no net cost savings for the APU. Aggressive usage of SP, or APUs where SP is not available, elimination of double-dipping and decreased base engine RPM should be encouraged in order to enhance fuel use and emission reductions during idling. There is the need for real-world data and consistent methodology in order to assess anti-idling strategies.
Micro-Scale On-Road Vehicle-Specific Emissions Measurement and Modeling
(2006-11-12) Zhang, Kaishan; Dr. M. Nagui Rouphail, Committee Member; Dr. Donald Van der vaart, Committee Member; Dr. B. Bibhuti Bhattacharyya, Committee Member; Dr. H. Christopher Frey, Committee Chair
The main objectives of this work are to quantify and compare intra- and inter-vehicle variability in fuel use and emissions and to develop capabilities of measuring and estimating fuel use and emissions at the micro-scale. This dissertation developed methodology to achieve the objectives, including experimental design for on-road data collection using a portable emission measurement system (PEMS), road grade estimation, evaluation of measurement accuracy, quantification of intra- and inter-vehicle variability in emissions, and micro-scale emissions modeling. A Light Detection and Ranging (LIDAR)-based method for road grade estimation was shown to be accurate and reliable. Measurement accuracy on a trip or mode basis was shown to be adequate. Routes, drivers, road grade, and time of day are significant sources of intra-vehicle variability. Significant inter-vehicle variability in emissions was observed, although only a small number of vehicles were tested and all belong to the same vehicle class. Thus, for accurate emission inventory development, both intra- and inter-vehicle variability should be taken into account. Consecutive averages were used for micro-scale emissions modeling to account for the response time of the PEMS. Choice of averaging time determines the model spatial and temporal resolution of prediction. Models for all pollutants are generally accurate, and precise in fuel use and CO2 emission estimation and moderately precise for other pollutants for various averaging times. Furthermore, models are capable of capturing the micro-scale events in emissions. Thus, the modeling schemes developed here can be used for a variety of applications including identification of the hotspots in emissions, transportation improvement programs on a corridor or intersection level, and more representative and accurate regional emission inventories development.
Operational Evaluation of In-Use Emissions and Fuel Consumption of B20 Biodiesel versus Petroleum Diesel-Fueled Onroad Heavy-duty Diesel Dump Trucks and Nonroad Construction Vehicles
(2007-12-18) Kim, Kangwook; Dr. H. Christopher Frey, Committee Chair; Dr. Nagui M. Rouphail, Committee Member; Dr. Donald R. van der Vaart, Committee Member; Dr. E. Downey Brill, Committee Member
Diesel vehicles contribute substantially to statewide emissions of NOx, an ozone precursor, and to particulate matter. North Carolina Department of Transportation (NCDOT) is conducting a pilot study to demonstrate the use of B20 biodiesel fuel on approximately 1,000 vehicles in selected areas of the state; there are plans to extend the use of B20 fuel to a much larger number of vehicles in all 100 counties in North Carolina. Real-world in-use onroad and nonroad emissions of selected heavy-duty diesel vehicles, including those fueled with B20 biodiesel and petroleum diesel, were measured during normal duty cycles using a portable emissions measurement system (PEMS). Each vehicle was tested for one day on B20 biodiesel and for one day on petroleum diesel, for a total of 68 days of field measurements. The vehicles were operated by drivers assigned by NCDOT. Each test was conducted over the course of an entire workshift, and there were approximately 2 to 10 duty cycles per shift. Each duty cycle is comprised of a uniquely weighted combination of operating modes based on vehicle speed, acceleration, and typical modes of activities. Average emission rates on a mass per time basis varied substantially among the operating modes. Average fuel use and emissions rates increased 26 to 35 percent when vehicles were loaded versus unloaded. The use of B20 instead of petroleum diesel lead to a slight decrease (approximately 2 to 10 percent depending on the vehicle) in NO emission rate and significant decreases (approximately 10 to 30 percent depending on the vehicle) for opacity, HC, and CO, respectively. These trends are similar to nonroad vehicles. Factors that were responsible for the observed variability in fuel use and emissions include: operating mode, vehicle size, engine tier and size, vehicle weight, and fuel. In particular, emission rates were also found to decrease significantly when comparing newer, higher tier vehicles to older ones. Recommendations were made regarding operating strategies to reduce emissions, choice of fuel, and the need for future work to collect real-world duty cycle data for other vehicle types.