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An operational scheme with fuel-lean and exhaust gas dilution in spark-ignited engines increases thermal efficiency and decreases NOx emission, while these operations inherently induce combustion instability and thus large cycle-to-cycle variation in engine. In order to stabilize combustion variations, the development of an advanced ignition system is becoming critical. To quantify the impact of spark-ignition discharge, ignitability tests were conducted in an optically accessible combustion vessel to characterize the flame kernel development of lean methane-air mixture with CO₂ simulating exhaust diluent. A shrouded fan was used to generate turbulence in the vicinity of J-gap spark plug and a Variable Output Ignition System (VOIS) capable of producing a varied set of spark discharge patterns was developed and used as an ignition source. The main feature of the VOIS is to vary the secondary current during glow discharge including naturally decaying and truncated with multiple strikes.

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.

One of the major challenges in multiobjective, multidisciplinary design optimization (MDO) is the long computational time required in evaluating the new designs' performances. To shorten the cycle time of product design, a data mining-based strategy is developed to improve the efficiency of heuristic optimization algorithms. Based on the historical information of the optimization process, clustering and classification techniques are employed to identify and eliminate the low quality and repetitive designs before operating the time-consuming design evaluations. The proposed method improves design performances within the same computation budget. Two case studies, one mathematical benchmark problem and one vehicle side impact design problem, are conducted as demonstration.

Ultrasonic fatigue tests (testing frequency around 20 kHz) have been conducted on four different cast aluminum alloys each with a distinct composition, heat treatment, and microstructure. Tests were performed in dry air, laboratory air and submerged in water. For some alloys, the ultrasonic fatigue lives were dramatically affected by the environment humidity. The effects of different factors like material composition, yield strength, secondary dendrite arm spacing and porosity were investigated; it was concluded that the material strength may be the key factor influencing the environmental humidity effect in ultrasonic fatigue testing. Further investigation on the effect of chemical composition, especially copper content, is needed.

Gas Metal Arc Welding (GMAW) is widely employed for joining relatively thick sheet steels in automotive body-in-white structures and frames. The GMAW process is very flexible for various joint geometries and has relatively high welding speed. However, fatigue failures can occur at welded joints subjected to various types of loads. Thus, vehicle design engineers need to understand the fatigue characteristics of welded joints produced by GMAW. Currently, automotive structures employ various advanced high strength steels (AHSS) such as dual-phase (DP) and transformation-induced plasticity (TRIP) steels to produce lighter vehicle structures with improved safety performance and fuel economy, and reduced harmful emissions. Relatively thick gages of AHSS are commonly joined to conventional high strength steels and/or mild steels using GMAW in current body-in-white structures and frames.

High cycle fatigue tests at a constant positive mean stress have been performed on a Al-Si-Cu cast aluminum alloy. The Random Fatigue Limit (RFL) model was employed to fit the probabilistic S-N curves based on Maximum Likelihood Estimate (MLE). Fractographic studies indicated that fatigue cracks in most specimens initiate from oxide films located at or very close to specimen surface. The RFL model was proved to be able to accurately capture the scatter in fatigue life. The cumulative density function (CDF) of fatigue life determined by RFL fit is found to be approximately equal to the complementary value of the CDF of the near-surface fatigue initiator size.

Advanced high strength steels (AHSS) have been widely accepted as a material of choice in the automotive industry to balance overall vehicle weight and stringent vehicle crash test performance targets. Combined with efficient use of geometry and load paths through shape and topology optimization, AHSS has enabled vehicle manufacturers to obtain the highest possible ratings in safety evaluations by the Insurance Institute for Highway Safety (IIHS) and the National Highway Traffic Safety Administration (NHTSA). In this study, vehicle CAE side impact models were used to evaluate three side impact crash test conditions (IIHS side impact, NHTSA LINCAP and FMVSS 214 side pole) and the IIHS roof strength test condition and to identify several key components affecting the side impact test performance. HyperStudy® optimization software and LS-DYNA® nonlinear finite element software were utilized for shape and gauge optimization.

A Ford 2.4-liter 115PS light-duty diesel engine was modified to allow solenoid control of the oil feed to the piston cooling jets, enabling these to be switched on or off on demand. The influence of the jets on piston temperatures, engine thermal state, gaseous emissions and fuel economy has been investigated. With the jets switched off, piston temperatures were measured to be between 23 and 88°C higher. Across a range of speed-load points, switching off the jets increased engine-out emissions of NOx typically by 3%, and reduced emissions of CO by 5-10%. Changes in HC were of the same order and were reductions at most conditions. Fuel consumption increased at low-speed, high-load conditions and decreased at high-speed, low-load conditions. Applying the results to the NEDC drive cycle suggests active on/off control of the jets could reduce engine-out emissions of CO by 6%, at the expense of a 1% increase in NOx, compared to the case when the jets are on continuously.

Reducing friction in crankshaft bearings during cold engine operation by heating the oil supply to the main gallery has been investigated through experimental investigations and computational modelling. The experimental work was undertaken on a 2.4l DI diesel engine set up with an external heat source to supply hot oil to the gallery. The aim was to raise the film temperature in the main bearings early in the warm up, producing a reduction in oil viscosity and through this, a reduction in friction losses. The effectiveness of this approach depends on the management of heat losses from the oil. Heat transfer along the oil pathway to the bearings, and within the bearings to the journals and shells, reduces the benefit of the upstream heating.

Finite Element (FE) models are widely used in automotive for vehicle design. Even with increasing speed of computers, the simulation of high fidelity FE models is still too time-consuming to perform direct design optimization. As a result, response surface models (RSMs) are commonly used as surrogates of the FE models to reduce the turn-around time. However, RSM may introduce additional sources of uncertainty, such as model bias, and so on. The uncertainty and model bias will affect the trustworthiness of design decisions in design processes. This calls for the development of stochastic model interpolation and extrapolation methods that can address the discrepancy between the RSM and the FE results, and provide prediction intervals of model responses under uncertainty.

Corrosion tendency is one of the major inhibitors for increased use of magnesium alloys in automotive structural applications. Moreover, systematic or standardized methods for evaluation of both general and galvanic corrosion of magnesium alloys, either as individual components or eventually as entire subassemblies, remains elusive, and receives little attention from professional and standardization bodies. This work reports outcomes from an effort underway within the U.S. Automotive Materials Partnership - ‘USAMP’ (Chrysler, Ford and GM) directed toward enabling technologies and knowledge base for the design and fabrication of magnesium-intensive subassemblies intended for automotive “front end” applications. In particular, subassemblies consisting of three different grades of magnesium (die cast, sheet and extrusion) and receiving a typical corrosion protective coating were subjected to cyclic corrosion tests as employed by each OEM in the consortium.

Since the beginning the world automotive industry looks for new technologies to improve the passengers' life inside vehicles, to optimize the consumption of fuel and to minimize the emission of pollutant. In the present study improvements in the vehicle acclimatization system for better cabin environmental conditions and reduction of fuel consumption were accomplished. The study included improvements in the air chamber and in the refrigeration cycle and was accomplished in a off-road vehicle model, with a bi-fuel engine of 1600 cm3, endowed with an acclimatization system with capacity of 1 TR (usual in this type of automobile). The tests of the acclimatization system performance were executed initially with the conventional system of air conditioning, without any modification (reference system). Along the development of the work modifications were introduced for the determination of the impact of these modifications in the system performance.

There has been a substantial increase in the use of advanced high strength steel (AHSS) in automotive structures in the last few years. The usage of these materials is projected to grow significantly in the next 5-10 years with the introduction of new safety and fuel economy regulations. AHSS are gaining popularity due to their superior mechanical properties and use in parts for weight savings potential, as compared to mild steels. These new materials pose significant manufacturing challenges, particularly for welding and stamping. Proper understanding of the weldability of these materials is critical for successful application on future vehicle programs. Due to the high strength nature of AHSS materials, higher weld forces and longer weld times are often needed to weld these advanced strength steels.

Effects of DOF and subjective method on evaluations of ride quality on the Ford Vehicle Vibration Simulator were studied. Seat track vibrations from 6 vehicles were reproduced on the 6 DOF seat shaker in a DOE with pitch and roll as factors. These appeared in two evaluations of ride/shake; semantic scaling by 30 subjects of 6 vehicles, and paired comparisons by 16 of the subjects on 3 of the vehicles. Both methods found significant vehicle, pitch and roll effects. Order dependence was shown for semantic scaling. The less susceptible paired comparison method gave a different ordering, and is thus preferred.

In the North American automotive industry, various advanced high strength steels (AHSS) are used to lighten vehicle structures, improve safety performance and fuel economy, and reduce harmful emissions. Relatively thick gages of AHSS are commonly joined to conventional high strength steels and/or mild steels using Gas Metal Arc Welding (GMAW) in the current generation body-in-white structures. Additionally, fatigue failures are most likely to occur at joints subjected to a variety of different loadings. It is therefore critical that automotive engineers need to understand the fatigue characteristics of welded joints. The Sheet Steel Fatigue Committee of the Auto/Steel Partnership (A/S-P) completed a comprehensive fatigue study on GMAW joints of both AHSS and conventional sheet steels including: DP590 GA, SAE 1008, HSLA HR 420, DP 600 HR, Boron, DQSK, TRIP 780 GI, and DP780 GI steels.

A cold turbocharger test facility was designed and developed at The Ohio State University to measure the performance characteristics under steady state operating conditions, investigate unsteady surge, and acquire acoustic data. A specific turbocharger is used for a thermodynamic analysis to determine the capabilities and limitations of the facility, as well as for the design and construction of the screw compressor, flow control, oil, and compression systems. Two different compression system geometries were incorporated. One system allows compressor performance measurements left of the surge line, while the other incorporates a variable-volume plenum. At the full plenum volume and a specific impeller tip speed, the temporal variation of the compressor inlet and outlet and the plenum pressures as well as the turbocharger speed is presented for stable, mild surge, and deep surge operating points.

ACOUSTOMIZE™ is a new method of acoustic evaluation used for the purpose of understanding and optimizing NVH performance of vehicles. The following paper documents a case study of the ACOUSTOMIZE™ test methodology on a passenger car BIW. This study includes an analysis of noise flow through BIW locations, a comparison of noise sound levels through BIW cavities with and without a sound treatment package and a comparison of the original cavity sealing design package consisting of baffles, tapes and baggies to low density polyurethane NVH Foam. The results of the study show detection of complex BIW pass throughs that the body leakage test (BLT) was not able to find. In addition, the data shows improved noise reduction with the low density polyurethane foam versus the original cavity sealing design package.

Soot formation and distribution inside the cylinder of a light-duty direct injection diesel engine, have been predicted using Kiva-3v CFD software. Pathlines of soot particles traced from specific in-cylinder locations and crank angle instants have been explored using the results for cylinder charge motion predicted by the Kiva-3v code. Pathlines are determined assuming soot particles are massless and follow charge motion. Coagulation and agglomeration have not been taken into account. High rates of soot formation dominate during and just after the injection. Oxidation becomes dominant after the injection has terminated and throughout the power stroke. Computed soot pathlines show that soot particles formed just below the fuel spray axis during the early injection period are more likely to travel to the cylinder wall boundary layer. Soot particles above the fuel spray have lesser tendency to be conveyed to the cylinder wall.

The effect of compression ratio on sensitivity to changes in start of injection and air-fuel ratio has been investigated on a single-cylinder DI diesel engine at fixed low and medium speeds and loads. Compression ratio was set to 17.9:1 or 13.7:1 by using pistons with different bowl sizes. Injection timing and air-to-fuel ratio were swept around a nominal map point at which gross IMEP and NOx values were matched for the two compression ratios. It was found that CO, HC and ISFC were higher at low compression ratio, but the soot/NOx trade-off improved and this could be exploited to reduce the fuel economy penalty. Sensitivity to inputs is generally similar, but high compression ratio tended to have steeper response gradients. Reducing compression ratio to 13.7 gave rise to a marked degradation of performance at light load, producing high CO emissions and a fall in combustion efficiency. This could be eased by reducing rail pressure, but the advantage in smoke emission was lost.