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The fuel consumption and emissions of diesel engines is strongly influenced by the injection rate pattern, which influences the in-cylinder mixing and combustion process. Knowing the exact injection rate is mandatory for an optimal diesel combustion development. The short injection time of no more than some milliseconds prevents a direct flow rate measurement. However, the injection rate is deduced from the pressure change caused by injecting into a fuel reservoir or pipe. In an ideal case, the pressure increase in a fuel pipe correlates with the flow rate. Unfortunately, real measurement devices show measurement inaccuracies and errors, caused by non-ideal geometrical shapes as well as variable fuel temperature and fuel properties along the measurement pipe. To analyze the thermal effect onto the measurement results, an available rate measurement device is extended with a flexible heating system as well as multiple pressure and temperature sensors.

The High Voltage Power Distribution Unit (PDU) is constructed of magnesium in support of Fuel Cell Electric Vehicle (FCEV) weight reduction efforts. The PDU distributes and controls a nominal 75 kilowatts of power generated by the Fuel Cell, the primary source of High Voltage power, to all the vehicle loads and accessories. The constraints imposed on the design of the PDU resulted in a component highly susceptible to general and galvanic corrosion. Corrosion abatement was the focus of the PDU redesign. This paper describes the redesign efforts undertaken by Ford personnel to improve the part robustness and corrosion resistance.

The performance of three way and NOx catalysts was evaluated on vehicles utilizing non-feedback fuel control and electronic feedback fuel control. The vehicles accumulated 80,450 km (50,000 miles) using fuels representing the extremes in hydrogen-carbon ratio available for commercial use. Feedback carburetion compared to non-feedback carburetion improved highway fuel economy by about 0.4 km/l (1 mpg) and reduced deterioration of NOx with mileage accumulation. NOx emissions were higher with the low H/C fuel in the three way catalyst system; feedback reduced the fuel effect on NOx in these cars by improving conversion efficiency with the low H/C fuel. Feedback had no measureable effect on HC and CO catalyst efficiency. Hydrocarbon emissions were lower with the low H/C fuel in all cars. Unleaded gasoline octane improver, MMT, at 0.015g Mn/l (0.06 g/gal) increased tailpipe hydrocarbon emissions by 0.05 g/km (0.08 g/mile).

A study was conducted using Ford's nine standard CFD calibration models as described in SAE paper 940323. The models are identical from the B-pillar forward but have different back end configurations. These models were created for the purpose of evaluating the effect of back end geometry variations on aerodynamic lift and drag. Detailed experimental data is available for each model in the form of surface pressure data, surface flow visualization, and wake flow field measurements in addition to aerodynamic lift and drag values. This data is extremely useful in analyzing the accuracy of the numerical simulations. The objective of this study was to determine the capability of a digital physics based commercial CFD code, PowerFLOW ® to accurately simulate the physics of the flow field around the car-like benchmark shapes.

The objective of this paper is to demonstrate that frequency domain methods for calculating structural response and fatigue damage can be more widely applicable than previously thought. This will be demonstrated by comparing results of time domain vs. frequency domain approaches for a series of fatigue/durability problems with increasing complexity. These problems involve both static and dynamic behavior. Also, both single input and multiple correlated inputs are considered. And most important of all, a variety of non-stationary loading types have been used. All of the example problems investigated are typically found in the automotive industry, with measured loads from the field or from the proving ground.

This paper presents the progress of an ongoing corrosion study of vehicle microenvironments. The study identifies the difference of corrosion microenvironments at various automotive proving grounds, using a sensor-equipped vehicle. A vehicle was instrumented for the proving ground test study. Various types of environmental sensors were installed at more than thirty-five sites on the vehicle. These sensors measured the temperature and relative humidity of the ambient air, and the temperature and time-of-wetness of the sites' surfaces. Cold rolled steel (CRS) and Zinc (Zn) corrosion rate sensors were also used in the experiments. The comparative analysis of vehicle microenvironments and corrosion rates of CRS and Zn, from three corrosion proving ground tests, will be discussed.

In order to reduce fuel consumption, companies have been looking at hybridizing vehicles. So far, two main hybridization options have been considered: electric and hydraulic hybrids. Because of light duty vehicle operating conditions and the high energy density of batteries, electric hybrids are being widely used for cars. However, companies are still evaluating both hybridization options for medium and heavy duty vehicles. Trucks generally demand very large regenerative power and frequent stop-and-go. In that situation, hydraulic systems could offer an advantage over electric drive systems because the hydraulic motor and accumulator can handle high power with small volume capacity. This study compares the fuel displacement of class 6 trucks using a hydraulic system compared to conventional and hybrid electric vehicles. The paper will describe the component technology and sizes of each powertrain as well as their overall vehicle level control strategies.

Two oxygenated fuels were evaluated on a single-cylinder diesel engine and compared to three hydrocarbon diesel fuels. The oxygenated fuels included canola biodiesel (canola methyl esters, CME) and CME blended with dibutyl succinate (DBS), both of which are or have the potential to be bio-derived. DBS was added to improve the cold flow properties, but also reduced the cetane number and net heating value of the resulting blend. A 60-40 blend of the two (60% vol CME and 40% vol DBS) provided desirable cold flow benefits while staying above the U.S. minimum cetane number requirement. Contrary to prior vehicle test results and numerous literature reports, single-cylinder engine testing of both CME and the 60-40 blend showed no statistically discernable change in NOx emissions relative to diesel fuel, but only when constant intake oxygen was maintained.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Combustion in modern spark-ignition (SI) engines is increasingly knock-limited with the wide adoption of downsizing and turbocharging technologies. Fuel autoignition conditions are different in these engines compared to the standard Research Octane Number (RON) and Motor Octane Numbers (MON) tests. The Octane Index, OI = RON - K(RON-MON), has been proposed as a means to characterize the actual fuel anti-knock performance in modern engines. The K-factor, by definition equal to 0 and 1 for the RON and MON tests respectively, is intended to characterize the deviation of modern engine operation from these standard octane tests. Accurate knowledge of K is of central importance to the OI model; however, a single method for determining K has not been well accepted in the literature.

With concerns over increasing worldwide demand for gasoline and greenhouse gases, many automotive companies are increasing their product lineup of vehicles to include flex-fuel vehicles that are capable of operating on fuel blends ranging from 100% gasoline up to a blend of 15% gasoline/85% ethanol (E85). For the purpose of this paper, data was obtained that will enable an evaluation relating to the effect the use of E85 fuel has on exhaust system surface temperatures compared to that of regular unleaded gasoline while the vehicle undergoes a typical drive cycle. Three vehicles from three different automotive manufacturers were tested. The surface of the exhaust systems was instrumented with thermocouples at specific locations to monitor temperatures from the manifold to the catalytic converter outlet. The exhaust system surface temperatures were recorded during an operation cycle that included steady vehicle speed operation; cold start and idle and wide open throttle conditions.

In this work, the effects of ozone, hydrogen, carbon monoxide, and exhaust gas recirculation (EGR) addition to Haltermann gasoline combustion were investigated. For these additives, laminar and turbulent flame speeds were experimentally determined using spherically propagating premixed flames in a constant volume combustion vessel. Two initial mixture pressures of Po = 1 and 5 bar, two initial mixture temperatures of 358 and 373 K and a range of equivalence ratios (Ф) from 0.5 to 1 were investigated. The additives were added as single, binary and ternary mixtures to Haltermann gasoline over a wide range of concentrations. For the stoichiometric mixture, the addition of 10% H2, 5% CO and 1000 ppm O3 shows remarkable enhancement (80%) in SL0compared to neat Haltermann gasoline. In addition, for this same blend, increasing the mixture initial temperature and pressure results in a significant increase in SL0compared to the neat gasoline.

In a recent study, quantitative measurements were presented of in-cylinder spatial distributions of mixture equivalence ratio in a single-cylinder light-duty optical diesel engine, operated with a non-reactive mixture at conditions similar to an early injection low-temperature combustion mode. In the experiments a planar laser-induced fluorescence (PLIF) methodology was used to obtain local mixture equivalence ratio values based on a diesel fuel surrogate (75% n-heptane, 25% iso-octane), with a small fraction of toluene as fluorescing tracer (0.5% by mass). Significant changes in the mixture's structure and composition at the walls were observed due to increased charge motion at high swirl and injection pressure levels. This suggested a non-negligible impact on wall heat transfer and, ultimately, on efficiency and engine-out emissions.

A correlation of aerodynamic wind tunnels was initiated between Chrysler, Ford and General Motors under the umbrella of the United States Council for Automotive Research (USCAR). The wind tunnels used in this correlation were the open jet tunnel at Chrysler's Aero Acoustic Wind Tunnel (AAWT), the open jet tunnel at the Jacobs Drivability Test Facility (DTF) that Ford uses, and the closed jet tunnel at General Motors Aerodynamics Laboratory (GMAL). Initially, existing non-competitive aerodynamic data was compared to determine the feasibility of facility correlation. Once feasibility was established, a series of standardized tests with six vehicles were conducted at the three wind tunnels. The size and body styles of the six vehicles were selected to cover the spectrum of production vehicles produced by the three companies. All vehicles were tested at EPA loading conditions. Despite the significant differences between the three facilities, the correlation results were very good.

Self-piercing rivet (SPR) joints are a key joining technology for lightweight materials, and they have been widely used in automobile manufacturing. Manual visual crack inspection of SPR joints could be time-consuming and relies on high-level training for engineers to distinguish features subjectively. This paper presents a novel machine learning-based crack detection method for SPR joint button images. Firstly, sub-images are cropped from the button images and preprocessed into three categories (i.e., cracks, edges and smooth regions) as training samples. Then, the Artificial Neural Network (ANN) is chosen as the classification algorithm for sub-images. In the training of ANN, three pattern descriptors are proposed as feature extractors of sub-images, and compared with validation samples. Lastly, a search algorithm is developed to extend the application of the learned model from sub-images into the original button images.

Brake squeal has been a chronic customer complaint, often appearing high on the list of items that reduce customers' satisfaction with their vehicles. Brake squeal can emanate from either a drum brake or a disc brake even though the geometry of the two systems is significantly different. A drum brake generates friction within a cylindrical drum interacting with two semi-circular linings. A disc brake consists of a flat disc and two flat pads. The observed squeal behavior in a vehicle differs somewhat between drum and disc brakes. A drum brake may have a loud noise coming from three or more squeal frequencies, whereas a disc brake typically has one or two major squeal frequencies making up the noise. A good understanding of the operational deflection shapes of the brake components during noise events will definitely aid in design to reduce squeal occurrences and improve product quality.

Striving for sustainable transportation solutions, hydrogen is often identified as a promising energy carrier and internal combustion engines are seen as a cost effective consumer of hydrogen to facilitate the development of a large-scale hydrogen infrastructure. Driven by efficiency and emissions targets defined by the U.S. Department of Energy, a research team at Argonne National Laboratory has worked on optimizing a spark-ignited direct injection engine for hydrogen. Using direct injection improves volumetric efficiency and provides the opportunity to properly stratify the fuel-air mixture in-cylinder. Collaborative 3D-CFD and experimental efforts have focused on optimizing the mixture stratification and have demonstrated the potential for high engine efficiency with low NOx emissions. Performance of the hydrogen engine is evaluated in this paper over a speed range from 1000 to 3000 RPM and a load range from 1.7 to 14.3 bar BMEP.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

Designing a durability test for an automatic transmission that appropriately reflects customer usage during the lifetime of the vehicle is a formidable task; while the transmission and its components must survive severe usage, overdesigning components leads to unnecessary weight, increased fuel consumption and increased emissions. Damage to transmission components is a function of many parameters including customer driving habits and vehicle and transmission characteristics such as weight, powertrain calibration, and gear ratios. Additionally, in some cases durability tests are required to verify only a subset of the total parameter space, for example, verifying only component modifications. Lastly, the ideal durability test is designed to impose the worst case loading conditions for the maximum number of internal components, be as short as practicable to reduce testing time, with minimal variability between tests in order to optimize test equipment and personnel resources.

A method of predicting brake specific fuel consumption characteristics from limited specifications of engine design has been investigated. For spark ignition engines operating on homogeneous mixtures, indicated specific fuel consumption based on gross indicated power is related to compression ratio and spark timing relative to optimum values. The influence of burn rate is approximately accounted for by the differences in spark timings required to correctly phase combustion. Data from engines of contemporary design shows that indicated specific fuel consumption can be defined as a generic function of relative spark timing, mixture air/fuel ratio and exhaust gas recirculation rate. The additional information required to generate brake specific performance maps is cylinder volumetric efficiency, rubbing friction, auxiliary loads, and exhaust back pressure characteristics.