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Due to the stringent requirements to reduce the tail pipe emissions of NOx, Selective Catalytic Reduction (SCR) systems are used to remove NOx using ammonia. When a urea solution is injected into the exhaust system, urea will undergo hydrolysis and decomposition reaction that produces ammonia. At the catalyst surface, ammonia will react with the exhaust gases to convert NOx into nitrogen, N2 and water, H2O. One of the challenging problems is to make sure the urea solution is available for the SCR system at cold start conditions. At extreme cold temperatures, the urea solution will begin to freeze at −12°C. At the start up of a vehicle under such low ambient temperatures, a heating system is used to provide the heat required for melting the frozen urea. Therefore, there will be a time lag between the vehicle start up and the availability of urea solution to the SCR system.

Dimensional variation simulation is a computer aided engineering (CAE) method that analyzes the statistical efforts of the component variation to the quality of the final assembly. The traditional tolerance analysis method and commercial CAE software are often based on the assumptions of the rigid part assembly. However, the vehicle functional attributes, such as, ride and handling, NVH, durability and reliability, require understanding the assembly quality under various dynamic conditions while achieving vehicle dimensional clearance targets. This paper presents the methods in evaluating and analyzing the impacts of the assembly variations for the vehicle dynamic performance. Basic linear tolerance stack method and advanced study that applies various CAE tools for the virtual quality analysis in the product and process design will be discussed.

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.

A snap-fit is a form-fitting joint, which is used to assemble plastic parts together. Snap-fits are available in different forms like a projecting clip, thicker section or legs in one part, and it is assembled to another part through holes, undercuts or recesses. The main function of the snap-fit is to hold the mating components, and it should withstand the vibration and durability loads. Snap-fits are easy to assemble, and should not fail during the assembling process. Based on the design, these joints may be separable or non-separable. The non- separable joints will withstand the loads till failure, while separable joints will withstand only for the design load. The insertion and the retention force calculation for the snaps are very essential for snap-fit design. The finite element analysis plays a very important role in finding the insertion and the retention force values, and also to predict the failure of the snaps and the mating components during this process.

Computer programs and models are playing an increasing role in simulating vehicle crashworthiness, dynamic, and fuel efficiency. To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively. For a successful implementation of Computer Aided Engineering (CAE) models as an integrated part of the current vehicle development process, it is necessary to develop objective validation metric that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results. However, most of the outputs of dynamic systems are multiple functional responses, such as time history series. This calls for the development of an objective metric that can evaluate the differences of the multiple time histories as well as the key features under uncertainty.

A copula-based approach for model bias characterization was previously proposed [18] aiming at improving prediction accuracy compared to other model characterization approaches such as regression and Gaussian Process. This paper proposes an adaptive copula-based approach for model bias identification to enhance the available methodology. The main idea is to use cluster analysis to preprocess data, then apply the copula-based approach using information from each cluster. The final prediction accumulates predictions obtained from each cluster. Two case studies will be used to demonstrate the superiority of the adaptive copula-based approach over its predecessor.

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.

Simulation based design optimization has become the common practice in automotive product development. Increasing computer models are developed to simulate various dynamic systems. Before applying these models for product development, model validation needs to be conducted to assess their validity. In model validation, for the purpose of obtaining results successfully, it is vital to select or develop appropriate metrics for specific applications. For dynamic systems, one of the key obstacles of model validation is that most of the responses are functional, such as time history curves. This calls for the development of a metric that can evaluate the differences in terms of phase shift, magnitude and shape, which requires information from both time and frequency domain. And by representing time histories in frequency domain, more intuitive information can be obtained, such as magnitude-frequency and phase-frequency characteristics.

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.

Connectivity has become an essential need for daily device users. With the car projected to be the “ultimate mobile device”, connectivity modules will eventually be mainstream in every car. Network providers are expanding their infrastructure and technology to accommodate the connected cars. Besides making voice and emergency calls the connected car will be sharing data with telematics service providers, back end systems and other vehicles. This trend will increase vehicle modules, complexity, entry points and vulnerabilities. This paper will present the current connected car architectures. The paper will present current architectural issues of the connected car and its vulnerabilities. The paper will present a new proposed architecture for the future connected car that enhances efficiency and security.

The SAE Fuel Cell Vehicle (FCV) Safety Working Group has been addressing FCV safety for over 9 years. The initial document, SAE J2578, was published in 2002. SAE J2578 has been valuable as a Recommended Practice for FCV development with regard to the identification of hazards and the definition of countermeasures to mitigate these hazards such that FCVs can be operated in the same manner as conventional gasoline internal combustion engine (ICE)-powered vehicles. SAE J2578 is currently being revised so that it will continue to be relevant as FCV development moves forward. For example, test methods were refined to verify the acceptability of hydrogen discharges when parking in residential garages and commercial structures and after crash tests prescribed by government regulation, and electrical requirements were updated to reflect the complexities of modern electrical circuits which interconnect both AC and DC circuits to improve efficiency and reduce cost.

A correlation study was performed between static wind tunnel testing and computational fluid dynamics (CFD) for a small hatchback vehicle, with the intent of evaluating a variety of different wheel and tire designs for aerodynamic forces. This was the first step of a broader study to develop a tool for assessing wheel and tire designs with real world (rolling road) conditions. It was discovered that better correlation could be achieved when actual tire scan data was used versus traditional smooth (CAD) tire geometry. This paper details the process involved in achieving the best correlation of the CFD prediction with experimental results, and describes the steps taken to include the most accurate geometry possible, including photogrammetry scans of an actual tire that was tested, and the level of meshing detail utilized to capture the fluid effects of the tire detail.

The intake and exhaust port design plays a substantial role in performance of combustion systems. The port design determines the volumetric efficiency and in-cylinder charge motion of the spark-ignited engine which influences the thermodynamic properties directly related to the power output, emissions, fuel consumption and NVH properties. Thus intake port has to be appropriately designed to fulfill the required charge motion and high flow performance. While turbulence intensity and air-mixture quality affect dilution tolerance and fuel economy as a result, breathing ability affects wide open throttle performance. Traditional approaches require experimental techniques to reach a target balance between the charge motion and breathing capacity. Such techniques do not necessarily result in an optimized solution.

SAE 8620 and other steels are typically used in the carburized condition for powertrain applications in the automotive industry, i.e., differential ring gears, camshafts, and transmission gears. Although current recommended carburizing practice involves normalizing the steel prior to carburizing, elimination of this normalizing treatment could lead to significant cost reductions. This research examines whether the normalizing process prior to carburizing could be eliminated without negatively affecting part performance. This study focused on the effects of the initial microstructure on the residual stress, retained austenite, and effective case depths of carburized SAE 8620 and PS-18 steels.

The focus of this study was to determine the residual stress and retained austenite profiles for carbonitrided and nitrocarburized SAE 1010 plain carbon steel and to relate these profiles to one another and to the distortion resulting from heat treatment. Navy C-ring specimens were used for the purpose of this study and X-ray diffraction techniques were used to measure both residual stress and retained austenite. The findings from this research are then applied to a manufacturing application involving the surface hardening of a thin shelled, plain carbon steel automotive component.

Stringent fuel economy and emissions regulations have driven development of new mixture preparation technologies and increased spark-ignition engine complexity. Additional degrees of freedom, brought about by devices such as cam phasers and charge motion control valves, enable greater range and flexibility in engine control. This permits significant gains in fuel efficiency and emission control, but creates challenges related to proper engine control and calibration techniques. Accurate experimental characterization of high degree of freedom engines is essential for addressing the controls challenge. In particular, this paper focuses on the evaluation of three experimental residual gas fraction measurement techniques for use in a spark ignition engine equipped with dual-independent variable camshaft phasing (VVT).

With increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the automotive gasoline fuel spray has become essential. The acquisition of accurate and repeatable spray data is even more critical when a combustion strategy such as gasoline direct injection is to be utilized. Without industry-wide standardization of testing procedures, large variablilities have been experienced in attempts to verify the claimed spray performance values for the Sauter mean diameter, Dv90, tip penetration and cone angle of many types of fuel sprays. A new SAE Recommended Practice document, J2715, has been developed by the SAE Gasoline Fuel Injection Standards Committee (GFISC) and is now available for the measurement and characterization of the fuel sprays from both gasoline direct injection and port fuel injection injectors.

This paper analyzes the difference in impact response of the forehead of the Hybrid III and THOR-NT dummies in free motion headform tests when a dummy strikes the interior trim of a vehicle. Hybrid III dummy head is currently used in FMVSS201 tests. THOR-NT dummy head has been in development to replace Hybrid III head. The impact response of the forehead of both the Hybrid III dummy and THOR dummy was designed to the same human surrogate data. Therefore, when the forehead of either dummy is impacted with the same initial conditions, the acceleration response and consequently the head Injury criterion (HIC) should be similar. A number of manufacturing variables can affect the impacted interior trim panels. This work evaluates the effect of process variation on the response in the form of Head Injury Criterion (HIC).