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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

Hydrogen is widely considered a promising fuel for future transportation applications for both, internal combustion engines and fuel cells. Due to their advanced stage of development and immediate availability hydrogen combustion engines could act as a bridging technology towards a wide-spread hydrogen infrastructure. Although fuel cell vehicles are expected to surpass hydrogen combustion engine vehicles in terms of efficiency, the difference in efficiency might not be as significant as widely anticipated [1]. Hydrogen combustion engines have been shown capable of achieving efficiencies of up to 45 % [2]. One of the remaining challenges is the reduction of nitric oxide emissions while achieving peak engine efficiencies. This paper summarizes research work performed on a single-cylinder hydrogen direct injection engine at Argonne National Laboratory.

As world-wide container volume increases and very large container ships emerge as a dominant player in the maritime cargo transport market, functional capabilities of container ports need to be greatly enhanced. To address this problem, KAIST is undertaking a project to design a novel container transport system, namely Mobile Harbor. Mobile Harbor refers to a system that can go out to a large container ship anchoring in the open sea, load and unload containers between the container ship and the Mobile Harbor, and transport them to their destinations. Designing Mobile Harbor presents a number of challenges as with many other large-scale engineering projects, especially at the beginning stage of the project.

The use of a diesel oxidation catalyst (DOC) in conjunction with a diesel particulate filter (DPF) is now a well-established aftertreatment system design for on-road heavy duty diesel. For non-road applications, the DOC must respond to the need for performance under more diverse and less favorable conditions, such as operation at low loads in cold weather. To choose a DOC technology for such applications, one must have practical and meaningful tests that address the specific catalytic functions of interest such as hydrocarbon oxidation to produce heat for regenerating DPF. This paper describes the development of an engine test protocol that focuses on resistance to the phenomenon known as quenching, the cessation of hydrocarbon (HC) oxidation that occurs when the exhaust temperature decreases below the light-off temperature of the catalyst. During development, the sensitivity and repeatability of the test were carefully scrutinized.

This study mainly focuses on developing an accurate tracking controller for the self-energizing clutch actuator (SECA) system consisting of a DC motor with an encoder applied on the automated manual transmission (AMT). In the position-based actuation of the SECA, abruptly increasing torque near the clutch kissing point during the clutch engagement process induces control input saturation and jerky response when a conventional feedback controller is applied. The proposed work resolves such issue and significantly increases the control accuracy of the actuator through the development of an effective H-infinity controller. The control performance is shown to be more effective than a simple PID controller via simulation and experiments using an AMT test bench equipped with SECA aided by d-SPACE and Matlab/Simulink.

This paper presents an adaptation method of equivalent factor in equivalent consumption minimization strategy (ECMS) of fuel cell hybrid electric vehicle (FCHEV) using hilly road information. Instantaneous optimization approach such as ECMS is one of real-time controllers. Furthermore, it is widely accepted that ECMS achieves near-optimum results with the selection of the appropriate equivalent factor. However, a lack of hilly road information no longer guarantees near-optimum results as well as charge-sustaining of ECMS under hilly road conditions. In this paper, first, an optimal control problem is formulated to derive ECMS analytical solution based on simplified models. Then, we proposed updating method of equivalent factor based on sensitivity analysis. The proposed method tries to mimic the globally optimal equivalent factor trajectory extracted from dynamic programming solutions.

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).

HiSiMo cast irons are frequently used as material for high temperature components in engines as e.g. exhaust manifolds and turbo chargers. These components must withstand severe cyclic mechanical and thermal loads throughout their life cycle. The combination of thermal transients with mechanical load cycles results in a complex evolution of damage, leading to thermomechanical fatigue (TMF) of the material and, after a certain number of loading cycles, to failure of the component. In Part I of the paper, a fracture mechanics model for TMF life prediction was developed based on results of uniaxial tests. In this paper (Part II), the model is formulated for three-dimensional stress states, so that it can be applied in a post-processing step of a finite-element analysis. To obtain reliable stresses and (time dependent plastic) strains in the finite-element calculation, a time and temperature dependent plasticity model is applied which takes non-linear kinematic hardening into account.

HiSiMo cast irons are frequently used as material for high temperature components in engines as e.g. exhaust manifolds and turbo chargers. These components must withstand severe cyclic mechanical and thermal loads throughout their service life. The combination of thermal transients with mechanical load cycles results in a complex evolution of damage, leading to thermomechanical fatigue (TMF) of the material and, after a certain number of loading cycles, to failure of the component. In this paper (Part I), the low-cycle fatigue (LCF) and TMF properties of HiSiMo are investigated in uniaxial tests and the damage mechanisms are addressed. On the basis of the experimental results a fatigue life model is developed which is based on elastic, plastic and creep fracture mechanics results of short cracks, so that time and temperature dependent effects on damage are taken into account.

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.

This paper focuses on modeling of the heavy-duty vehicle drivetrain with automatic transmission by using dual clutch scheme. The planetary gear set in the automatic transmission is complicated structure and difficult to understand. The advantage of the dual clutch scheme is that it can be used to represent the complex planetary gear set intuitively, which is a great help to understand the gear shifting process. It is also suitable for being used in the controller due to its low order. Some conditions are required to convert the planetary gear set to the dual clutch model. The heavy-duty vehicle driveline can be converted to the dual clutch model due to its heavy engine and vehicle inertia. This paper also proposes system parameter estimation methods to represent the driveline model. The main parameters are lumped inertia, lumped gear efficiency, output shaft compliance and friction coefficient of clutches.

Demand for electrified vehicles is increasing due to increased environmental pollution regulations and interest in highly efficient vehicles. According to these demands, research on electrified vehicles equipped with Dual Clutch Transmission (DCT) has been actively conducted for the purpose of improving energy efficiency of electrified powertrain, maximizing acceleration performance, and increasing maximum speed. However, since DCT requires clutch to clutch shifting, it is difficult to control drive torque and slip speed using two clutch actuators and a power source input. In order to solve this, a study on a multivariable shift controller has been conducted. However, this study chose a heuristic planning method to control the two outputs. However, since the slip speed and drive torque are coupled, it is necessary to tune the reference for every shift scenario, as well as create unnecessary control inputs or degrade shift control performance.

An aqueous urea solution is used as the source of ammonia for selective catalytic reduction (SCR) of NOx to reduce the emissions of NOx in the exhaust of diesel vehicles. However, the decomposition of urea into ammonia is not always complete, resulting in solid urea deposit formation in the decomposition tube or on the SCR catalyst. These solid deposits can impede the flow of the exhaust gases (and uniformity of NH3 supply) and reduce SCR catalyst performance over time. To minimize the formation of urea deposit and to meet EPA NOx emission regulations, it is important to understand the chemistry of formation or removal of the deposit in the decomposition tube and SCR catalyst. In this report, IR spectroscopy, UV-visible spectroscopy, thermogravimetric analysis and elemental analysis have been used to determine the chemical composition of the solid urea deposits formed by the thermal decomposition of urea.

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.

Operator training using a weapon in a real-world environment is risky, expensive, time-consuming, and restricted to the given environment. In addition, governments are under intense scrutiny to provide security, yet they must also strive for efficiency and reduce spending. In other words, they must do more with less. Virtual simulation, is usually employed to solve these limitations. As the operator is trained to maximize weapon effectiveness, the effectiveness-focused training can be completed in an economical manner. Unfortunately, the training is completed in limited scenarios without objective levels of training factors for an individual operator to optimize the weapon effectiveness. Thus, the training will not be effective. For overcoming this problem, we suggest a methodology on guiding effectiveness-focused training of the weapon operator through usability assessments, big data, and Virtual and Constructive (VC) simulations.

In a Spark-Ignited engine, there will come a point, as load is increased, where the unburned air-fuel mixture undergoes auto-ignition (knock). The onset of knock represents the upper limit of engine output, and limits the extent of engine downsizing / boosting that can be implemented for a given application. Although effective at mitigating knock, requiring high octane fuel is not an option for most markets. Retarding spark timing can extend the high load limit incrementally, but is still bounded by limits for exhaust gas temperature, and spark retard results in a notable loss of efficiency. Likewise, enriching the air-fuel mixture also decreases efficiency, and has profound negative impacts on engine out emissions. In this current work, a Direct-Injected, Boosted, Spark-Ignited engine with Variable Valve Timing was tested under steady state high load operation. Comparisons were made among three fuels; an 87 AKI, a 91 AKI, and a 110 AKI off-road only race fuel.

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.

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.