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In light-duty direct-injection (DI) diesel engines, combustion chamber geometry influences the complex interactions between swirl and squish flows, spray-wall interactions, as well as late-cycle mixing. Because of these interactions, piston bowl geometry significantly affects fuel efficiency and emissions behavior. However, due to lack of reliable in-cylinder measurements, the mechanisms responsible for piston-induced changes in engine behavior are not well understood. Non-intrusive, in situ optical measurement techniques are necessary to provide a deeper understanding of the piston geometry effect on in-cylinder processes and to assist in the development of predictive engine simulation models. This study compares two substantially different piston bowls with geometries representative of existing technology: a conventional re-entrant bowl and a stepped-lip bowl. Both pistons are tested in a single-cylinder optical diesel engine under identical boundary conditions.

During the course of emissions and fuel economy (FE) testing, vehicles that are calibrated to meet Tier 3 emissions requirements currently must demonstrate compliance on Tier 3 E10 fuel while maintaining emissions capability with Tier 2 E0 fuel used for FE label determination. Tier 3 emissions regulations prescribe lower sulfur E10 gasoline blends for the U.S. market. Tier 3 emissions test fuels specified by EPA are required to contain 9.54 volume % ethanol and 8-11 ppm sulfur content. EPA Tier 2 E0 test fuel has no ethanol and has nominal 30 ppm sulfur content. Under Tier 3 rules, Tier 2 E0 test fuel is still used to determine FE. Tier 3 calibrations can have difficulty meeting low Tier 3 emissions targets while testing with Tier 2 E0 fuel. Research has revealed that the primary cause of the high emissions is deactivation of the aftertreatment system due to sulfur accumulation on the catalysts.

A laboratory study was performed to assess the potential capability of TWC+LNT/SCR systems to satisfy the Tier 2, Bin 2 emission standards for lean-burn gasoline applications. It was assumed that the exhaust system would need a close-coupled (CC) TWC, an underbody (U/B) TWC, and a third U/B LNT/SCR converter to satisfy the emission standards on the FTP and US06 tests while allowing lean operation for improved fuel economy during select driving conditions. Target levels for HC, CO, and NOx during lean/rich cycling were established. Sizing studies were performed to determine the minimum LNT/SCR volume needed to satisfy the NOx target. The ability of the TWC to oxidize the HC during rich operation through steam reforming was crucial for satisfying the HC target.

A laboratory study was performed to assess the potential capability of passive TWC+SCR systems to satisfy the Tier 2, Bin 2 emission standards for lean-burn gasoline applications. In this system, the TWC generates the NH3 for the SCR catalyst from the feedgas NOx during rich operation. Therefore, this approach benefits from high feedgas NOx during rich operation to generate high levels of NH3 quickly and low feedgas NOx during lean operation for a low rate of NH3 consumption. It was assumed that the exhaust system needed to include a close-coupled (CC) TWC, an underbody (U/B) TWC, and an U/B SCR converter to satisfy the emission standards during the FTP and US06 tests while allowing lean operation for improved fuel economy during select driving conditions. Target levels for HC, CO, and NOx during lean/rich cycling were established. With a 30 s lean/10 s rich cycle and 200 ppm NO lean, 1500 ppm NO rich and the equivalent of 3.3 L of SCR volume were required to satisfy the NOx target.

Optimization of heavy materials like steel, in order to create a lighter vehicle, it is a major goal among most automakers, since heavy vehicles simply cannot compete with a lightweight model's fuel economy. Thinking this way, this paper shows a case study where the Size Optimization technique is applied to a front floor reinforcement. The reinforcement is used by two different vehicles, a subcompact and a crossover Sport Utility Vehicle (SUV), increasing the problem complexity. The Size Optimization technique is supported by Finite Element Method (FEM) tools. FEM in Computer Aided Engineering (CAE) is a numerical method for solving engineering problems, and its use can help to optimize prototype utilization and physical testing.

Engine oils are subjected to a series of industry standard engine dynamometer tests to measure their wear protection capability, sludge and varnish formation tendencies, and fuel efficiency among several other performance attributes before they are approved for use in customer engines. However, these performance attributes are measured at the end of tests and therefore, do not provide any information on how the properties have changed during the tests. In one of our previous studies it was observed that engine oil samples collected from fleet vehicles after 12,000 mile drain interval showed 10-15 % lower friction and more importantly, an order of magnitude lower wear rate than those of fresh oils. It was also observed that the composition of the tribochemical films formed was quite different on the surface tested with the drain oils from those formed with fresh oils.

This paper describes SHEV, a computer program created to simulate hybrid electric vehicles. SHEV employs the time-stepping technique in order to evaluate energy flow in series hybrids, and makes use of a unique method in order to speed up the fuel economy estimation. This estimation method is a refinement of the “state of charge matching” method and is explained in detail. The graphic user interfaces employed in SHEV make it easy to use and give it a look similar to regular Windows‚ applications. This paper also gives some examples of the screens created by the program, depicts its main flowchart, and describes a battery model optimized for this application.

Reduced engine idle speed reduces fuel consumption but requires active idle speed control (ISC) to avoid stalls due to accessory load disturbances. For gasoline engines, spark advance is used in conjunction with air flow for the idle speed control. However, for spark control to be effective the nominal spark timing has to be retarded from the optimal timing to allow spark to increase torque. This offsets the fuel consumption benefit from lower speeds. During lean homogenous operating modes, Fuel Assisted ISC (FA-ISC) uses fuel to increase torque (similar to diesel and gasoline stratified charge) eliminating the need for the retarded nominal spark. The engine then operates close to optimal spark and the lean air fuel limit for optimal fuel economy.

Ford Motor Company has developed a full hybrid electric vehicle with a power-split hybrid powertrain. There are constraints imposed by the high voltage system in such an HEV, that do not exist in conventional vehicles. A significant controls problem that was addressed in the Ford Escape and Mercury Mariner Hybrids was the determination of the desired powertrain operating point such that the vehicle attributes of fuel economy, performance and drivability are met, while satisfying these new constraints. This paper describes the control system that addressed this problem and the tests that were designed to verify its operation.

The Hydra-Matic 6T70 is General Motors first model of a new, two-variant front wheel drive (FWD) six speed automatic transmission family. The second variant is a higher capacity model, the 6T75. The transmission was co-developed with Ford Motor Company. The 6F50 is the Ford variant that aligns with the GM 6T70 transmission. Approximately eighty five percent of the hardware is shared or common between the GM and Ford transmission variants. Ford will also have a higher capacity variant the 6F55 to align with the GM 6T75. The first GM application is the Saturn Aura for the 2007 Model Year. The Ford Edge and Lincoln MKX in MY 2007 will be the first applications for the 6F50. While the Hydra-Matic and Ford FWD six-speed family was designed with two variants in mind, the designed in modularity requires only changes to the second and third axis and case housings depending on specific torque requirements. This modular design enables a tremendous amount of part sharing.

Fuel economy and federal safety regulations are driving automotive companies to use Dual Phase and other Advanced High Strength Steels (AHSS) in vehicle body structures. Joining and assembly plays a crucial role in the selection of these steels. Specifications are available for the resistance spot welding (RSW) of lower strength sheet steels, covering many aspects of the welding process from the stabilization procedure to endurance testing. Currently, specifications in the automotive industry for RSW with AHSS are limited. It is well known that welding of a thickness ratio greater than 1:2 poses a challenge. To utilize thinner gauge AHSS panels on body-in-white, welding schedules to join the thin to thick sheet steel stack-up are needed. Most of the existing published work was conducted on uncoated sheets and welded to the same thickness.

The relation cost versus performance in the design of an automobile is crucial for its success. These two characteristics, much like the project development timing, are closely related to the attributes that the new design must achieve (e.g. weight, fuel economy, torsional stiffness, NVH, safety, etc.). In this respect, the design optimization of body reinforcements (i.e. part thickness, quantity of reinforcements, and number of spot welds) contributes greatly to a sound and robust project concept. This paper describes one application of 6-Sigma methodology to evaluate the performance of different configurations of seat belt reinforcements resulting in an optimized concept that achieved the proposed performance targets with weight and sub-assembly complexity reduction. Using a Design of Experiments (DOE) and Finite Element Analysis (FEA), each proposal was evaluated for its resistance to plastic deformation.

Engine and aftertreatment models have been developed in support of gasoline direct injection (GDI) engine development and aftertreatment system design. A brief overview of the engine models that were used to project emissions and fuel economy performance for the GDI engine is presented. Additionally, the construction and validation of a NOx trap aftertreatment model is described in considerable detail. The insights and increased understanding which have been gained regarding the trade-offs between engine out emission targets, aftertreatment performance, and emission constrained fuel economy benefits for direct injection gasoline engines are reviewed and discussed.

Data from two engines with distinct stratified-charge combustion systems are presented. One uses an air-forced injection system with a bowl-in-piston combustion chamber. The other is a liquid-only, high-pressure injection system which uses fluid dynamics coupled with a shaped piston to achieve stratification. The fuel economy and emission characteristics were very similar despite significant hardware differences. The contributions of indicated thermal efficiency, mechanical friction, and pumping work to fuel economy are investigated to elucidate where the efficiency gains exist and in which categories further improvements are possible. Emissions patterns and combustion phasing characteristics of stratified-charge combustion are also discussed.

Development of the Sequence VIB dynamometer engine test procedure for evaluating the fuel efficiency benefits of engine oils has recently been completed. This test was designed as an improvement over its predecessor, the Sequence VIA test. It evaluates fuel economy using a range of boundary/mixed and hydrodynamic lubrication stages selected to better represent a wider range of engines. In addition to determining “fresh oil” fuel economy, the new test determines fuel efficiency retention after a second oil aging stage that corresponds to 6437 - 9674 km (4,000 - 6,000 miles) of pre-certification aging of engine oils in vehicles and is representative of customer use. This paper describes the selection of aging conditions and length.

The newly developed Sequence VIB engine dynamometer test for measuring the ability of engine oils to improve engine fuel efficiency was designed as an improvement on its predecessor, the Sequence VIA test. The Sequence VIB test features an additional, extended oil aging to correspond to aging of engine oils in certification vehicles and in customer use, and a new set of boundary/mixed and hydrodynamic lubrication stages to better represent a wider range of engines. Five fuel economy measurement stages were chosen for the Sequence VIB test from a larger set of prototype stages, based on extensive friction modeling of engines, analysis of Sequence VIA data on reference oils, and operational considerations. Time factors for these stages were derived based on a mini-mapping of engines considering engine operating conditions in the Metro/Highway Federal fuel economy test procedure (FTP M/H) and the estimated market volume of each engine-vehicle.

High gas prices combined with demand for improved fuel economy have prompted increased interest in diesel engine applications for both light-duty and heavy-duty vehicles. The development of aftertreatment systems for these vehicles requires significant investments of capital and time. A reliable and robust qualification testing procedure will allow for more rapid development with lower associated costs. Qualification testing for DPFs has its basis in methods similar to DOCs but also incorporates a PM loading method and regeneration testing of loaded samples. This paper examines the effects of accelerated loading using a PM generator and compares PM generator loaded DPFs to engine dynamometer loaded samples. DPFs were evaluated based on pressure drop and regeneration performance for samples loaded slowly and for samples loaded under accelerated conditions. A regeneration reactor was designed and built to help evaluate the DPFs loaded using the PM generator and an engine dynamometer.

In recent years, HCCI (Homogeneous Charge Compression Ignition) combustion concept has attracted attention due to its potential for high fuel efficiency and low emissions. The essence of HCCI combustion is auto ignition of a very lean, homogeneous air-fuel mixture. However it leads to a major challenge for control engineers – controlling combustion timing to achieve required torque and optimal fuel consumption. There is a need for a simplified HCCI engine model to guide control strategy development. This paper presents such a control oriented model for a “heated intake air” HCCI engine concept that uses two streams of air (cold and hot) to achieve a variable temperature at intake valve closing.

Ford Motor Company has developed a full hybrid electric vehicle with a dual-drive hybrid powertrain configuration that has great potential to overcome some attribute deficiencies in existing hybrid powertrain architectures. This paper first provides an overview of the dual-drive hybrid electric vehicle architecture and its primary operating modes. The paper then presents the energy management control system that selects operating modes and desired powertrain operating points to improve fuel efficiency. Finally, experimental results from a dual-drive hybrid prototype vehicle are used to demonstrate the fuel efficiency improvement.

The desire for improved vehicle fuel economy, driven by high gas prices and concerns over energy independence, have sparked interest and demand for hybrid electric vehicles. Hybrid electric vehicle propulsion systems exhibit complex interactions which need to be understood in order to maximize fuel economy over the range of operating modes. Model-based development processes which use vehicle system models capable of representing the functional behaviors with embedded controls are needed for fast, efficient design of vehicle control systems which manage overall energy usage. Model-based vehicle system development processes have been employed for a Dual Drive HEV system. The process for creating these vehicle system models is described along with an approach for using these models to develop HEV systems. Details of key subsystem models and the process for integration of full vehicle implementation level controls are discussed.