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The development of PM and NOx reduction system with the combination of DOC included DPF and SCR catalyst in addition to the AOC sub-assembly for NH3 slip protection is described. DPF regeneration strategy and manual regeneration functionality are introduced with using ITH, HCI device on the EUI based EGR, VGT 12.3L diesel engine at the CVS full dilution tunnel test bench. With this system, PM and NOx emission regulation for JPNL was satisfied and DPF regeneration process under steady state condition and transient condition (JE05 mode) were successfully fulfilled. Manual regeneration process was also confirmed and HCI control strategy was validated against the heat loss during transient regeneration mode. Presenter Seung-il Moon

Engine operating strategies typically geared towards higher fuel economy and lower NOx widely affect exhaust composition and temperature. These exhaust variables critically drive the performance of After Treatment (AT) components, and hence should guide their screening and selection. Towards this end, the effect of H2 level in diesel exhaust on the performance of a Diesel Oxidation Catalyst (DOC) was studied using flow reactor experiments, vehicle emission measurements and mathematical models. Vehicle chassis dynamometer data showed that exhaust from light-duty and heavy-duty diesel trucks contained very little to almost no H2 (FTP average CO/H2 ∼ 40 to 70) as compared to that of a gasoline car exhaust (FTP average CO/H2 ∼ 3). Two identical flow reactor experiments, one with H2 (at CO/H2 ∼ 3) and another with no H2 in the feed were designed to screen DOCs under simulated feed gas conditions that mimicked these two extremes in the exhaust H2 levels.

A kinetic carbon monoxide (CO) emission model is developed to simulate engine out CO emissions for conventional diesel combustion. The model also incorporates physics governing CO emissions for low temperature combustion (LTC). The emission model will be used in an integrated system level model to simulate the operation and interaction of conventional and low temperature diesel combustion with aftertreatment devices. The Integrated System Model consists of component models for the diesel engine, engine-out emissions (such as NOx and Particulate Matter), and aftertreatment devices (such as DOC and DPF). The addition of CO emissions model will enhance the capability of the Integrated System Model to predict major emission species, especially for low temperature combustion. In this work a CO emission model is developed based on a two-step global kinetic mechanism [8].

Two different types of mesh used for diesel combustion with the KIVA-4 code are compared. One is a well established conventional KIVA-3 type polar mesh. The other is a non-polar mesh with uniform size throughout the piston bowl so as to reduce the number of cells and to improve the quality of the cell shapes around the cylinder axis which can contain many fuel droplets that affect prediction accuracy and the computational time. This mesh is specialized for the KIVA-4 code which employs an unstructured mesh. To prevent dramatic changes in spray penetration caused by the difference in cell size between the two types of mesh, a recently developed spray model which reduces mesh dependency of the droplet behavior has been implemented. For the ignition and combustion models, the Shell model and characteristic time combustion (CTC) model are employed.

Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

Biodiesel-blended fuel is increasingly becoming available for diesel engines. Due to seasonal and economic factors, biodiesel available in filling stations can be sourced from varying feedstocks. Moreover, biodiesel may not contain the minimum oxidative stability required by the time it is used by the automotive consumer. With fuel dilution of engine oil accelerated by post-injection of fuel for regeneration of diesel particulate filters, it is necessary to investigate whether different biodiesel feedstocks or stabilities can affect engine oil properties. In this work, SAE 15W-40 CJ-4 is diluted with B20 fuel, where the B20 was prepared with soy methyl ester (SME) B100 with high Rancimat oxidative stability, SME B100 with low oxidative stability, and lard methyl ester (LME). The oils were then subjected to laboratory aging simulating severe drive cycles. At intermediate aging times, samples were obtained and additional B20 was added to simulate on-going fuel dilution.

A 2005 prototype diesel aftertreatment system consisting of diesel oxidation catalysts (DOC), Cu/zeolite Selective Catalytic Reduction (SCR) catalyst, and Catalyzed Diesel Particulate Filter (CDPF) was aged to an equivalent of 120k mi on an engine dynamometer using an aging cycle that incorporated both city and highway driving modes. The program demonstrated durable reduction in particulate matter (PM) and nitrogen oxides (NOx) emissions to federal Tier 2 levels on a 6000 lbs light-duty truck application. Very low sulfur diesel fuel (∼15 ppm) enabled lower PM emissions, reduced the fuel penalty associated with the emission control system, and improved long-term system durability. A total of 643 filter regenerations occurred during the aging that raised the entire catalyst system to high temperatures on a regular basis. After testing the aged system on a 6000 lbs light-duty diesel truck, a post mortem analysis was completed on core samples taken from the DOC, SCR catalyst, and filter.

Reactivity-controlled compression ignition (RCCI) has been shown to be capable of providing improved engine efficiencies coupled with the benefit of low emissions via in-cylinder fuel blending. Much of the previous body of work has studied the benefits of RCCI operation using high injection pressures (e.g., 500 bar or greater) with common rail injection (CRI) hardware. However, low-pressure fueling technology is capable of providing significant cost savings. Due to the broad market adoption of gasoline direct injection (GDI) fueling systems, a market-type prototype GDI injector was selected for this study. Single-cylinder light-duty engine experiments were undertaken to examine the performance and emissions characteristics of the RCCI combustion strategy with low-pressure GDI technology and compared against high injection pressure RCCI operation. Gasoline and diesel were used as the low-reactivity and high-reactivity fuels, respectively.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

This paper presents a combined numerical and experimental investigation of the characteristics of spark discharge in a spark-ignition engine. The main objective of this work is to gain insights into the spark discharge process and early flame kernel development. Experiments were conducted in an inert medium within an optically accessible constant-volume combustion vessel. The cross-flow motion in the vessel was generated using a previously developed shrouded fan. Numerical modeling was based on an existing discharge model in the literature developed by Kim and Anderson. However, this model is applicable to a limited range of gas pressures and flow fields. Therefore, the original model was evaluated and improved to predict the behavior of spark discharge at pressurized conditions up to 45 bar and high-speed cross-flows up to 32 m/s. To accomplish this goal, a parametric study on the spark channel resistance was conducted.

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

Fuel lean combustion and exhaust gas dilution are known to increase the thermal efficiency and reduce NOx emissions. In this study, experiments are performed to understand the effect of equivalence ratio on flame kernel formation and flame propagation around the spark plug for different low turbulent velocities. A series of experiments are carried out for propane-air mixtures to simulate engine-like conditions. For these experiments, equivalence ratios of 0.7 and 0.9 are tested with 20 percent mass-based exhaust gas recirculation (EGR). Turbulence is generated by a shrouded fan design in the vicinity of J-spark plug. A closed loop feedback control system is used for the fan to generate a consistent flow field. The flow profile is characterized by using Particle Image Velocimetry (PIV) technique. High-speed Schlieren visualization is used for the spark formation and flame propagation.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

In order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

Increasing regulatory demand for efficiency has led to development of novel combustion modes such as HCCI, GCI and RCCI for gasoline light duty engines. In order to realize HCCI as a compression ignition combustion mode system, in-cylinder compression temperatures must be elevated to reach the autoignition point of the premixed fuel/air mixture. This should be co-optimized with appropriate fuel formulations that can autoignite at such temperatures. CFD combustion modeling is used to model the auto ignition of gasoline fuel under compression ignition conditions. Using the fully detailed fuel mechanism consisting of thousands of components in the CFD simulations is computationally expensive. To overcome this challenge, the real fuel is represented by few major components of create a surrogate fuel mechanism. In this study, 9 variations of gasoline fuel sets were chosen as candidates to run in HCCI combustion mode.

Past experimental studies conducted by the current authors on a 13 liter 16.7:1 compression ratio heavy-duty diesel engine have shown that diesel-Compressed Natural Gas (CNG) Reactivity Controlled Compression Ignition (RCCI) combustion targeting low NOx emissions becomes progressively difficult to control as the engine load is increased. This is mainly due to difficulty in controlling reactivity levels at higher loads. For the current study, CFD investigations were conducted in CONVERGE using the SAGE combustion solver with the application of the Rahimi mechanism. Studies were conducted at a load of 5 bar BMEP to validate the simulation results against RCCI experimental data. In the low load study, it was found that the Rahimi mechanism was not able to predict the RCCI combustion behavior for diesel injection timings advanced beyond 30 degCA bTDC. This poor prediction was found at multiple engine speed and load points.

Gasoline compression ignition (GCI) technology shows the potential to obtain high thermal efficiencies while maintaining low soot and NOx emissions in light-duty engine applications. Recent experimental studies and numerical simulations have indicated that high reactivity gasoline-like fuels can further enable the benefits of GCI combustion. However, there is limited empirical data in the literature studying the gasoline compression ignition process at relevant in-cylinder conditions, which are required for further optimizing combustion system designs. This study investigates the temporal and spatial evolution of the compression ignition process of various high reactivity gasoline fuels with research octane numbers (RON) of 71, 74 and 82, as well as a conventional RON 97 E10 gasoline fuel. A ten-hole prototype gasoline injector specifically designed for GCI applications capable of injection pressures up to 450 bar was used.

Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.