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This paper describes the joint development by Tenneco and Pi Shurlok of a complete diesel engine aftertreatment system for controlling particulate matter emissions. The system consists of a DOC, DPF, sensors, controller and an exhaust fuel injection system to allow active DPF regeneration. The mechanical components were designed for flow uniformity, low backpressure and component durability. The overall package is intended as a complete PM control system solution for OEMs, which does not require any significant additions to the OEM's engine control strategies and minimizes integration complexity. Thus, to make it easier to adapt to different engine platforms, ranging from small off-road vehicle engines to large locomotive engines, model-based control algorithms were developed in preference to map-based controls.

An experimental study was performed to develop a more fundamental understanding of the effects of secondary air injection (SAI) on exhaust gas emissions and catalyst light-off characteristics during cold start of a modern SI engine. The effects of engine operating parameters and various secondary air injection strategies such as spark retardation, fuel enrichment, secondary air injection location and air flow rate were investigated to understand the mixing, heat loss, and thermal and catalytic oxidation processes associated with SAI. Time-resolved HC, CO and CO₂ concentrations were tracked from the cylinder exit to the catalytic converter outlet and converted to time-resolved mass emissions by applying an instantaneous exhaust mass flow rate model. A phenomenological model of exhaust heat transfer combined with the gas composition analysis was also developed to define the thermal and chemical energy state of the exhaust gas with SAI.

One of the issues in stamping of advanced high strength steels (AHSS) is the stretch bending fracture on a sharp radius (commonly referred to as shear fracture). Shear fracture typically occurs at a strain level below the conventional forming limit curve (FLC). Therefore it is difficult to predict in computer simulations using the FLC as the failure criterion. A modified Mohr-Coulomb (M-C) fracture criterion has been developed to predict shear fracture. The model parameters for several AHSS have been calibrated using various tests including the butter-fly shaped shear test. In this paper, validation simulations are conducted using the modified (M-C) fracture criterion for a dual phase (DP) 780 steel to predict fracture in the stretch forming simulator (SFS) test and the bending under tension (BUT) test. Various deformation fracture modes are analyzed, and the range of usability of the criterion is identified.

The adoption of the electronic controlled steering systems with new technologies has been extended in recent years. They have interactions with other complex vehicle subsystems and it is a hard task for the vehicle developer to find the best solution from huge number of the combination of parameter settings with track tests. In order to improve the efficiency of the steering system development, the authors had developed a steering bench test method for steering system using a Hardware-In-the-Loop Simulation (HILS). In the steering HILS system, vehicle dynamics simulation and the tie rod axial force calculation are required at the same time in the real-time simulation environment. The accuracy of the tie rod axial force calculation is one of the key factors to reproduce the vehicle driving condition. But the calculation cannot be realized by a commercial software for the vehicle dynamics simulation.

The rotary engine provides high power density compared to piston engine, but one of its downside is higher oil consumption. A model of the oil seals is developed to calculate internal oil consumption (oil leakage from the crankcase through the oil seals) as a function of engine geometry and operating conditions. The deformation of the oil seals trying to conform to housing distortion is calculated to balance spring force, O-ring and groove friction, and asperity contact and hydrodynamic pressure at the interface. A control volume approach is used to track the oil over a cycle on the seals, the rotor and the housing as the seals are moving following the eccentric rotation of the rotor. The dominant cause of internal oil consumption is the non-conformability of the oil seals to the housing distortion generating net outward scraping, particularly next to the intake and exhaust port where the housing distortion valleys are deep and narrow.

The rotary engine provides high power density compared to piston engine, but one of its downside is higher oil consumption. In order to better understand oil transport, a laser induced fluorescence technique is used to visualize oil motion on the side of the rotor during engine operation. Oil transport from both metered oil and internal oil is observed. Starting from inside, oil accumulates in the rotor land during inward motion of the rotor created by its eccentric motion. Oil seals are then scraping the oil outward due to seal-housing clearance asymmetry between inward and outward motion. Cut-off seal does not provide an additional barrier to internal oil consumption. Internal oil then mixes with metered oil brought to the side of the rotor by gas leakage. Oil is finally pushed outward by centrifugal force, passes the side seals, and is thrown off in the combustion chamber.

Piston rings are large contributors to friction losses in internal combustion engines. To achieve higher engine efficiency, low friction ring packs that can maintain good sealing performance must be designed. To support this effort, simulation tools have been developed to model the performance of piston rings during engine operation. However, the challenge of predicting oil consumption, blow by, and ring pack friction with sufficient accuracy remains. This is mostly due to the complexity of this system. Ring dynamics, deformation, interaction with liner and piston, gas and lubricant flow must all be studied together to make relevant predictions. In this paper, a new curved beam finite element model of piston rings is proposed. Ring structural deformation and contact with the liner are treated on two separate grids. A comparison with ring models in the literature and analytical solutions shows that it can provide accurate results efficiently.

As the piston pin works under significant mechanical load, it is susceptible to wear, seizure, and structural failure, especially in heavy duty internal combustion engines. It has been found that the friction loss associated with the pin is comparable to that of the piston, and can be reduced when the interface geometry is properly modified. However, the mechanism that leads to such friction reduction, as well as the approaches towards further improvement, remain unknown. This work develops a piston pin lubrication model capable of simulating the interaction between the pin, the piston, and the connecting rod. The model integrates dynamics, solid contact, oil transport, and lubrication theory, and applies an efficient numerical scheme with second order accuracy to solve the highly stiff equations. As a first approach, the current model assumes every component to be rigid.

Technologies for improving the fuel economy of gasoline engines have been vigorously developed in recent years for the purpose of reducing CO2 emissions. Increasing the compression ratio for improving thermal efficiency and downsizing the engine based on fuel-efficient operating conditions are good examples of technologies for enhancing gasoline engine fuel economy. A direct-injection system is adopted for most of these engines. Direct injection can prevent knocking by lowering the in-cylinder temperature through fuel evaporation in the cylinder. Therefore, direct injection is highly compatible with downsized engines that frequently operate under severe supercharging conditions for improving fuel economy as well as with high compression ratio engines for which susceptibility to knocking is a disadvantage.

In the Big Data era, the capability in statistical and probabilistic data characterization, data pattern identification, data modeling and analysis is critical to understand the data, to find the trends in the data, and to make better use of the data. In this paper the fundamental probability concepts and several commonly used probabilistic distribution functions, such as the Weibull for spectrum events and the Pareto for extreme/rare events, are described first. An event quadrant is subsequently established based on the commonality/rarity and impact/effect of the probabilistic events. Level of measurement, which is the key for quantitative measurement of the data, is also discussed based on the framework of probability. The damage density function, which is a measure of the relative damage contribution of each constituent is proposed. The new measure demonstrates its capability in distinguishing between the extreme/rare events and the spectrum events.

This article is concerned with identification of true stress-strain curve under biaxial tension of thermoplastic polymers. A new type of biaxial tension attachment was embedded first in a universal material test machine, which is able to transform unidirectional loading of the test machine to biaxial loading on the specimen with constant velocity. Cruciform specimen geometry was optimized via FE modeling. Three methods of calculating true stress in biaxial tension tests were compared, based on incompressibility assumption, linear elastic theory and inverse engineering method, respectively. The inverse engineering method is more appropriate for thermoplastic polymers since it considers the practical volume change of the material during biaxial tension deformation. The strategy of data processing was established to obtain biaxial tension true stress-strain curves of different thermoplastic polymers.

Technologies for improving the fuel economy of gasoline engines have been vigorously developed in recent years for the purpose of reducing CO2 emissions. Increasing the compression ratio is an example of a technology for improving the thermal efficiency of gasoline engines. A significant issue of a high compression ratio engine for improving fuel economy and low-end torque is prevention of knocking under a low engine speed. Knocking is caused by autoignition of the air-fuel mixture in the cylinder and seems to be largely affected by heat transfer from the intake port and combustion chamber walls. In this study, the influence of heat transfer from the walls of each part was analyzed by the following three approaches using computational fluid dynamics (CFD) and experiments conducted with a multi-cooling engine system. First, the temperature rise of the air-fuel mixture by heat transfer from each part was analyzed.

The first 3 cycles in the cold crank-start process at 20°C are studied in a GDI engine. The focus is on the dependence of the HC and PM/PN emissions of each cycle on the injection strategy and combustion phasing of the current and previous cycles. The PM/PN emissions per cycle decrease by more than an order of magnitude as the crank-start progresses from the 1st to the 3rd cycle, while the HC emissions stay relatively constant. The wall heat transfer, as controlled by the combustion phasing, during the previous cycles has a more significant influence on the mixture formation process for the current cycle than the amount of residual fuel. The results show that the rise in HC emissions caused by the injection spray interacting with the intake valves and piston crown is reduced as the cranking process progresses. Combustion phasing retard significantly reduces the PM emission. The HC emissions, however, are relatively not sensitive to combustion phasing in the range of interest.

A new ring pack model has been developed based on the curved beam finite element method. This paper describes the first part of this model: simulating gas pressure in different regions above piston skirt and ring dynamic behavior of two compression rings and a twin-land oil control ring. The model allows separate grid divisions to resolve ring structure dynamics, local force/pressure generation, and gas pressure distribution. Doing so enables the model to capture both global and local processes at their proper length scales. The effects of bore distortion, piston secondary motion, and groove distortion are considered. Gas flows, gas pressure distribution in the ring pack, and ring structural dynamics are coupled with ring-groove and ring-liner interactions, and an implicit scheme is employed to ensure numerical stability. The model is applied to a passenger car engine to demonstrate its ability to predict global and local effects on ring dynamics and oil transport.

The adoption of electric vehicles (EVs) has been announced worldwide with the aim of reducing CO2 emissions. However, a significant increase in electricity demand by EVs might impact the stable operation of the existing power grid. Meanwhile, EV charging is acceptable to most users if it is completed by the time of the next driving event. From the viewpoint of power grid operators, flexibility for shifting the timing of EV charging would be advantageous, including making effective use of renewable energy. In this work, an EV model and simulation tool were developed to make clear how the total charging demand of all EVs in use will be influenced by future EV specifications (e.g., charge power) and installation of charging infrastructure. Among the most influential factors, EV charging behavior according to use cases and regional characteristics were statistically analyzed based on the real-world usage data of over 14, 000 EVs and incorporated in the simulation tool.

The aim of this study is to gain a better understanding of the mechanism of knocking with respect to flame propagation behavior based on 3D simulations conducted with the Universal Coherent Flamelet Model. Flame propagation behavior under the influence of in-cylinder flow was analyzed on the basis of the calculated results and experimental visualizations. Tumble and swirl flows were produced in the cylinder by inserting various baffle plates in the middle of the intake port. A comparison of the measured and calculated flame propagation behavior showed good agreement for various in-cylinder flow conditions. The results indicate that in-cylinder flow conditions vary the flame propagation shape from the initial combustion period and strongly influence the occurrence of knocking.

This paper proposes a method of estimating road friction and tire slip angle in a cornering maneuver. The method can estimate front tire road friction accurately at low lateral acceleration because it is based on the tire self-aligning torque (SAT) that exhibits high sensitivity to road friction at low slip angles. Road friction and tire slip angle, which are mutually interdependent, are estimated simultaneously using an extended Kalman filter designed around a model describing the relationship between road friction and SAT and a vehicle lateral dynamic model. The front tire SAT is calculated with a mathematical model that describes the torque transmission characteristics from the electric power steering torque to SAT. Therefore, the proposed method is readily applicable to production vehicles. Results of an experimental study show that the change in road friction is instantaneously estimated at low lateral acceleration.

For diesel engine, lower compression ratio has been demanded to improve fuel consumption, exhaust emission and maximum power recently. However, low compression ratio engine might have combustion instability issues under cold temperature condition, especially just after engine started. As a first step of this study, cold temperature combustion was investigated by in-cylinder pressure analysis and it found out that higher heat release around top dead center, which was mainly contributed by pilot injection, was the key factor to improve engine speed fluctuation. For further understanding of combustion in cold condition, particularly mixture formation near a glow plug, 3D CFD simulation was applied. Specifically for this purpose, TI (Time-scale Interaction) combustion model has been developed for simulating combustion phenomena. This model was based on a reasonable combustion mode, taking into account the characteristic time scale of chemical reactions and turbulence eddy break-up.

A robotic driver has been designed on the basis of an analysis of a human driver's action in following a given driving schedule. The self-learning algorithm enables the robot to learn the vehicle characteristics without human intervention. Based on learned relationships, the robotic driver can determine an appropriate accelerator position and execute other operations through sophisticated calculations using the future scheduled vehicle speed and vehicle characteristics data. Compensation is also provided to minimize vehicle speed error. The robotic driver can reproduce the same types of exhaust emission and fuel economy data obtained with human drivers with good repeatability. It doesn't require long preparation time. Thereby making it possible to reduce experimentation work in the vehicle development process while providing good accuracy and reliability.

In order to understand better the operation of spark-ignition engines during the warm-up period, a computer model had been developed which simulates the thermal processes of the engine. This model is based on lumped thermal capacitance methods for the major engine components, as well as the exhaust system. Coolant and oil flows, and their respective heat transfer rates are modeled, as well as friction heat generation relations. Piston-liner heat transfer is calculated based on a thermal resistance method, which includes the effects of piston and ring material and design, oil film thickness, and piston-liner crevice. Piston/liner crevice changes are calculated based on thermal expansion rates and are used in conjunction with a crevice-region unburned hydrocarbon model to predict the contribution to emissions from this source.