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Global demand for alternative fuels to combat rising energy costs has sparked a renewed interest in catalysts that can effectively remediate NOx emissions resulting from combustion of a range of HC based fuels. Because many of these new engine technologies rely on lean operating environments to produce efficient power, the resulting emissions are also present in a lean atmosphere. While HCs are easily controlled in such environments, achieving high NOx conversion to N2 has continued to elude fully satisfactory solution. Until recently, most approaches have relied on catalysts with precious metals to either store NOx and subsequently release it as N2 under rich conditions, or use NH3 SCR catalysts with urea injection to reduce NOx under lean conditions. However, new improvements in Ag based technologies also look very promising for NOx reduction in lean environments.

Low-cost lean NOx aftertreatment is one of the main challenges facing high-efficiency gasoline and diesel engines operating with lean mixtures. While there are many candidate technologies, they all offer tradeoffs. We have investigated a multi-component Dual SCR aftertreatment system that is capable of obtaining NOx reduction efficiencies of greater than 90% under lean conditions, without the use of precious metals or urea injection into the exhaust. The Dual SCR approach here uses an Ag HC-SCR catalyst followed by an NH3-SCR catalyst. In bench reactor studies from 150 °C to 500 °C, we have found, for modest C/N ratios, that NOx reacts over the first catalyst to predominantly form nitrogen. In addition, it also forms ammonia in sufficient quantities to react on the second NH3-SCR catalyst to improve system performance. The operational window and the formation of NH3 are improved in the presence of small quantities of hydrogen (0.1–1.0%).

A single-cylinder engine was used to study the potential of a high-efficiency combustion concept called gasoline direct-injection compression-ignition (GDCI). Low temperature combustion was achieved using multiple injections, intake boost, and moderate EGR to reduce engine-out NOx and PM emissions engine for stringent emissions standards. This combustion strategy benefits from the relatively long ignition delay and high volatility of regular unleaded gasoline fuel. Tests were conducted at 6 bar IMEP - 1500 rpm using various injection strategies with low-to-moderate injection pressure. Results showed that triple injection GDCI achieved about 8 percent greater indicated thermal efficiency and about 14 percent lower specific CO2 emissions relative to diesel baseline tests on the same engine. Heat release rates and combustion noise could be controlled with a multiple-late injection strategy for controlled fuel-air stratification. Estimated heat losses were significantly reduced.

Computer simulation was used as a complement to crash and injury field data analysis and physical sled and barrier tests to investigate and predict the spinal injuries of a rear impact in an IndyCar. The model was expected to relate the spinal loads to the observed injuries, thereby predicting the probability and location of spinal fractures. The final goal is to help reduce the fracture risk by optimizing the seat and restraint system design and the driver's position using computer modeling and sled testing. MADYMO Full FE Human Body Model (HBM) was selected for use because of its full spinal structural details and its compatibility with the vehicle and restraint system models. However, the IndyCar application imposed unique challenges to the HBM. First, the driver position in a race car is very different from that in a typical passenger car.

Implementation of real-time combustion feedback for use in closed-loop combustion control is a technology that has potential to assist in the successful production implementation of advanced diesel combustion modes. Low-temperature, pre-mixed diesel combustion is presently of interest because it offers the ability to lower the engine-out emissions of oxides of nitrogen (NOx) and particulate matter (PM). The need for lowering these two emissions is driven by tighter regulations enacted worldwide, especially the NOx limits in the United States. Reducing engine-out emissions eases the need for additional exhaust aftertreatment devices and their associated cost and mass. In this paper we will describe an experimental cylinder pressure-based control system and present both steady-state and transient results from a diesel engine employing a pre-mixed type of combustion.

In recent years, gasoline direct injection (GDi) engines have been popular due to their inherent potential for reduction of exhaust emissions and fuel consumption to meet stringent EPA standards. These engines require high-pressure fuel injection in order to improve the atomization process and accelerate mixture preparation. The high-pressure fuel pump is an essential component in the GDi system. Therefore, understanding the flow characteristics of this device and its associated behavior is critical for improving the performance of this category of engines. In this paper, the fluid flow characteristics in a high-pressure single-piston pump for use in GDi engines are analyzed using 1-D LMS Imagine.Lab AMESim system and 3-D Ansys Fluent computational fluid dynamics (CFD) models. The flow rate of the fuel pump under various cam speeds has been examined along with characteristics of the pump's control valve.

The need for improved emissions control in lean exhaust to meet tightening, world-wide NOx emissions standards has led to the development of selective catalytic reduction of NOx with ammonia as a major technology for emissions control. Current systems are being designed to use a solution of urea (32.5 wt %) dissolved in water or Diesel Exhaust Fluid (DEF) as the ammonia source. While DEF or AdBlue® is widely used as a source of ammonia, it has a number of issues at low temperatures, including freezing below −12 °C, solid deposit formation in the exhaust, and difficulties in dosing at exhaust temperatures below 200 °C. Additionally creating a uniform ammonia concentration can be problematic, complicating exhaust packaging and usually requiring a discrete mixer.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

Automotive rollover is a complex mechanical phenomenon. In order to understand the mechanism of rollover and develop any potential countermeasures for occupant protection, efficient and repeatable laboratory tests are necessary. However, these tests are not well understood and are still an active area of research interest. It is not always easy or intuitive to estimate the necessary initial and boundary conditions for such tests to assure repeatability. This task can be even more challenging when rollover is a second or third event (e.g. frontal impact followed by a rollover). In addition, often vehicle and occupant kinematics need to be estimated a-priori, first for the safe operation of the crew and equipment safety, and second for capturing and recording the event. It is important to achieve the required vehicle kinematics in an efficient manner and thus reduce repetitive tests. Mathematical modeling of the phenomenon can greatly assist in understanding such kinematics.

A new single-brick Ba + alkali metals NOx-Trap catalyst has been developed to replace a two-brick NOx-Trap system containing a downstream three-way catalyst. Major development efforts include: 1) platinum group metals selection for higher HC oxidation with potassium-containing washcoat, 2) alumina and ceria selection, and Rh architecture design for more efficient NOx reduction and 3) NiO to suppress H2S odor. Mitsubishi Motors' 1.8L GDI™ with this Delphi new NOx-Trap catalyst with H2S control achieves J-LEV standard with less cost and lower backpressure compared to the previous model. It is further discovered that incorporation of NiO into the NOx-Trap washcoat is effective for H2S control during sulfur purge but has a negative impact on thermal durability and sulfur resistance. Further study to improve this trade-off has been made and preliminary results of an advanced washcoat design are presented in this paper. Details will be reported in a future publication.

Regulatory and market pressures continue to challenge the automotive industry to develop technologies focused on reducing exhaust emissions and improving fuel economy. This paper introduces a practical model, which evaluates the economic value of various technologies based on their ability to reduce fuel consumption, improve emissions or provide consumer benefits such as improved performance. By evaluating the individual elements of economic value as viewed by the OEM manufacturer, while keeping the end consumer in mind, technology selection decisions can be made. These elements include annual fuel usage, vehicle performance, mass reduction and emissions, among others. The following technologies are discussed and evaluated: gasoline direct injection, variable valvetrain technologies, common-rail diesel and hybrid vehicles.

An integrated optimization system has been developed to combine optimization algorithms with Finite Element Analysis for airbag design. A number of industry standard software packages are employed to work in coherence to complete the optimization procedure automatically with minimal user intervention. The system can be easily tailored to fit multiple performance requirements and various design constraints for different airbag systems. Compared with the commonly used Design of Experiment (DOE) method, time and computer resources requirements are greatly curtailed. The integrated optimization system was successfully used in single-chamber and dual-chamber airbag optimizations. The results proved the effectiveness of the system and demonstrated its capability in product design.

2-step variable valve actuation using early-intake valve closing is a strategy for high fuel economy on spark-ignited gasoline engines. Two discrete valve-lift profiles are used with continuously variable cam phasing. 2-step VVA systems are attractive because of their low cost/benefit, relative simplicity, and ease-of-packaging on new and existing engines. A 2-step VVA system was designed and integrated on a 4-valve-per-cylinder 4.2L line-6 engine. Simulation tools were used to develop valve lift profiles for high fuel economy and low NOx emissions. The intake lift profiles had equal lift for both valves and were designed for high airflow & residual capacity in order to minimize valvetrain switching during the EPA drive cycle. It was determined that an enhanced combustion system was needed to maximize fuel economy benefit with the selected valve lift profiles. A flow-efficient chamber mask was developed to increase in-cylinder tumble motion and combustion rates.

The intensity of a combustion flame ionization current signal (ionsense) can be used to monitor and control combustion in individual cylinders during a cold engine start. The rapid detection of poor or absence of combustion can be used to determine fuel delivery corrections that may prevent engine stalls. With the ionsense cold start control active, no start failures were recorded even when the initially (prior to ionsense correction) commanded fueling had failed to produce a combustible mixture. This new dimension in fuel control allows for leaner cold start calibrations that would still be robust against the possible use of low volatility gasoline. Consequently, when California Phase 2 fuel is used, cold start hydrocarbon emissions could be lowered without the risk of an engine stall if the appropriate fuel is replaced with a less volatile one.

Robust Engineering techniques developed by Taguchi have traditionally applied to the optimization of engineering designs. Robust Engineering methods also may be applied to software testing of ECU algorithms. The net result is an approach capable of improving the software algorithm in one of two ways. First the approach can identify the range of areas which prove problematic to the software such that a robust solution may be developed. Conversely, the approach can be used as a general strategy to verify that the software is robust over the range of inputs tested. The robust engineering methods applied to software testing utilize orthogonal array experiments to test software over a range of inputs. The actual software trials are best performed in the simulation environment and also via automated test hardware in the loop configurations in realtime. This paper outlines a process for applying Robust Engineering methods to software testing.

A new optimal control strategy for dealing with braking actuator failures in a vehicle equipped with a brake-by-wire and steer-by- wire system is described. The main objective of the control algorithm during the failure mode is to redistribute the control tasks to the functioning actuators, so that the vehicle performance remains as close as possible to the desired performance in spite of a failure. The desired motion of the vehicle in the yaw plane is determined using driver steering and braking inputs along with vehicle speed. For the purpose of synthesizing the control algorithm, a non-linear vehicle model is developed, which describes the vehicle dynamics in the yaw plane in both linear and non-linear ranges of handling. A control allocation algorithm determines the control inputs that minimize the difference between the desired and actual vehicle motions, while satisfying all actuator constraints.

Active/semi-active suspension control of a passenger vehicle is a classic problem involving multiple-objectives, all of which cannot be simultaneously achieved without compromises between ride and handling performance. Traditionally, suspension control tuning has been a subjective process that involves tuning of hundreds of parameters. This paper attempts to add some level of objectivity to the tuning philosophy by posing the ride/handling trade-off as a multi-constrained, multi-objective optimization problem and solving it using a mixed-H2/H∞ control synthesis technique to obtain a pareto-optimal solution. The multi-variable constrained optimization problem involves minimization of body control metrics subject to constraints defined by wheel-control metrics (a measure of road-holding capability). Simulation as well as road-test results clearly demonstrate the effectiveness and impact the proposed control strategy has on improving ride and handling performance.

Close-coupled or manifold catalysts have been extensively employed to reduce emissions during cold start by achieving quick catalyst light-off. These catalysts must have good thermal durability, high intrinsic light-off activity and high HC/CO/NOx conversions at high temperature and flow conditions. A number of studies have been dedicated to engine control, manifold design and converter optimization to reduce cold start emissions. The current paper focuses on the effect of catalyst design parameters and their performance response to different engine operating conditions. Key design parameters such as catalyst formulation (CeO2 vs. non CeO2), precious metal loading and composition (Pd vs. Pd/Rh), washcoat loading, catalyst thermal mass, substrate properties and key application (in use) parameters such as catalyst aging, exhaust A/F ratio, A/F ratio modulation, exhaust temperature, temperature rise rate and exhaust flow rate were studied on engine dynamometers in a systematic manner.

Segmented, Silicon-Carbide Diesel Particulate Filters appear to be automotive industry's popular choice for reducing particulate emissions of Diesel Engines, particularly for light duty platforms. Since flow resistance represents an important performance feature of a filter, it is important that reasonable prediction tools for such filters are developed for use in their development, design, applications and regeneration control. A model for predicting pressure drop of segmented filters is presented here: an existing, well-accepted pressure drop model for monolithic (non-segmented) filters is customized to one for a segmented filter using a ‘weighted number of inlet channels’ based on equivalent filtration wall area of a monolithic filter. Flow resistance data collected experimentally on segmented filters are used to demonstrate the accuracy of the new model.