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With increasing energy prices and concerns about the environmental impact of greenhouse gas (GHG) emissions, a growing number of national governments are putting emphasis on improving the energy efficiency of the equipment employed throughout their transportation systems. Within the U.S. transportation sector, energy use in commercial vehicles has been increasing at a faster rate than that of automobiles. A 23% increase in fuel consumption for the U.S. heavy duty truck segment is expected from 2009 to 2020. The heavy duty vehicle oil consumption is projected to grow while light duty vehicle (LDV) fuel consumption will eventually experience a decrease. By 2050, the oil consumption rate by LDVs is anticipated to decrease below 2009 levels due to CAFE standards and biofuel use. In contrast, the heavy duty oil consumption rate is anticipated to double. The increasing trend in oil consumption for heavy trucks is linked to the vitality, security, and growth of the U.S. and global economies.

The world-wide commercial vehicle industry is faced with numerous challenges to reduce oil consumption and greenhouse gases, meet stringent emissions regulations, provide customer value, and improve safety. This work focuses on the new U.S. regulation of greenhouse gas (GHG) emissions from commercial vehicles and diesel engines and the most likely technologies to meet future anticipated standards while improving transportation freight efficiency. In the U.S., EPA and NHTSA have issued a joint proposed GHG rule that sets limits for CO2 and other GHGs from pick-up trucks and vans, vocational vehicles, semi-tractors, and heavy duty diesel engines. This paper discusses and compares different technologies to meet GHG regulations for diesel engines based on considerations of cost, complexity, real-world fidelity, and environmental benefit.

The influence of various diesel fuel properties on the steady state emissions and performance of a Cummins light-duty (ISB) engine modified for single cylinder operation has been studied at the mid-load “cruise” operating condition. Designed experiments involving independent manipulation of both fuel properties and engine control parameters have been used to build statistical engine response models. The models were then applied to optimize for the minimum fuel consumption subject to specific constraints on emissions and mechanical limits and also to estimate the optimum engine control parameter settings and fuel properties. The study reveals that under the high EGR, diffusion-burn dominated conditions encountered during the experiments, NOx is impacted by cetane number and the distillation characteristics. Lower T50 (mid-distillation temperature) resulted in simultaneous reductions in both NOx and smoke, and higher cetane number provided an additional small NOx benefit.

As the world market develops for biodiesel fuels, it is likely that a wider variety of biodiesels will become available, both locally and globally, and require engines to operate on a wider variety of fuels than experienced today. At the same time, tighter emissions regulations and a drive for improved fuel economy have focused interest on advanced combustion modes such as HCCI or PCCI, which are known to be more sensitive to fuel properties. This research covers two series of biodiesel fuels. In the first, B20 blends of natural methyl esters derived from palm, coconut, rape, soy, and mustard were evaluated at light load in an HCCI research engine to determine combustion and performance characteristics. These fuels showed performance differences between the biodiesels and the base #2 ULSD fuel, but did not allow separation of chemical effects due to the small number of fuels and correlation of various properties.

Effects of methyl ester biodiesel fuel blends on NOx emissions are studied experimentally and analytically. A precisely controlled single cylinder diesel engine experiment was conducted to determine the impact of a 20% blend of soy methyl ester biodiesel (B20) on NOx emissions. The data were then used to calibrate KIVA chemical kinetics models which were used to determine how the biodiesel blend affects NOx production during the combustion process. In addition, the impact on the engine control system of the lower specific energy content of biodiesel was determined. Both factors, combustion and controls, must be taken into account when determining the net NOx effect of biodiesel compared to conventional diesel fuel. Because the magnitude and even direction of NOx effect changes with engine load, the NOx effect associated with burning biodiesel blends over a duty cycle depends on the duty cycle average power and fuel cetane number.

In previous publications, Singh et al. [1, 2] have shown that direct integration of CFD with a detailed chemistry auto-ignition model (KIVA-CHEMKIN) performs reasonably well for predicting combustion, emissions, and flame structure for stratified diesel engine operation. In this publication, it is shown that the same model fails to predict combustion for partially premixed dual-fuel engines. In general, models that account for chemistry alone, greatly under-predict cylinder pressure. This is shown to be due to the inability of such models to simulate a propagating flame, which is the major source of heat release in partially premixed dual-fuel engines, under certain operating conditions. To extend the range of the existing model, a level-set-based, hybrid, auto-ignition/flame-propagation (KIVA-CHEMKIN-G) model is proposed, validated and applied for both stratified diesel engine and partially premixed dual-fuel engine operation.

Analysis of the cold-starting performance of diesel engines requires the development of advanced models to describe the multicomponent nature of the fuel as well as the spray impingement and wall film behavior. A new approach to modeling the multicomponent nature of commercial fuels was implemented. This model is based on a continuous distribution using a probability density function, rather than the use of discrete components, to capture more accurately the entire range of composition in commercial fuels. The model was applied to single droplet calculations to validate the predictions against experimental results. Previous discrete component wall-film modeling has been extended to include the continuous multicomponent fuel representation. A significant factor that has received little attention in analyzing the cold-start performance of diesel engines is the spray impingement angle and location. This has been investigated using the modified KIVA code.