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In this paper, we propose algorithms for cost minimization of physical wires that are used to connect electronic devices in the vehicle. The wiring cost is one of the most important drivers of electrical architecture selection. Our algorithms perform wire routing from a source device to a destination device through harnesses, by selecting the optimized wire size. In addition, we provide optimized splice allocation with limited constraints. Based on the algorithms, we develop a tool which is integrated into an off-the-shelf optimization and workflow system-level design tool. The algorithms and the tool provide an efficient, flexible, scalable, and maintainable approach for cost analysis and architecture selection.

Traditional vehicle air conditioning systems condition the entire cabin to a comfortable range of temperature and humidity regardless of the number of passengers in the vehicle. The A/C system is designed to have enough capacity to provide comfort for transient periods when cooling down a soaked car. Similarly for heating, the entire cabin is typically warmed up to achieve comfort. Localized heating and cooling, on the other hand, focuses on keeping the passenger comfortable by forming a micro climate around the passenger. This is more energy efficient since the system only needs to cool the person instead of the entire cabin space and cabin thermal mass. It also provides accelerated comfort for the passenger during the cooling down periods of soaked cars. Additionally, the system adapts to the number of passengers in the car, so as to not purposely condition areas that are not occupied.

A comparison of welding techniques was performed to determine the most effective method for producing aluminum tailor-welded blanks for high volume automotive applications. Aluminum sheet was joined with an emphasis on post weld formability, surface quality and weld speed. Comparative results from several laser based welding techniques along with friction stir welding are presented. The results of this study demonstrate a quantitative comparison of weld methodologies in preparing tailor-welded aluminum stampings for high volume production in the automotive industry. Evaluation of nearly a dozen welding variations ultimately led to down selecting a single process based on post-weld quality and performance.

Response Surface Models are often used as a surrogate for expensive black-box functions during optimization to reduce computational cost. Often, the CAE analysis models are highly nonlinear and multi-modal. A response surface approximation of such analysis as a result is highly multi-modal; i.e. it contains multiple local optima. A gradient-based optimizer working with such a response surface will often converge to the nearest local optimum. There does not exist any method to guarantee a global optima for non-convex multi-modal functions. For such problems, we propose an efficient algorithm to find as many distinct local optima as possible. The proposed method is specifically designed to work in large dimensions (about 100 ∼ 1000 design variables and similar number of constraints) and can identify most of the locally optimal solutions in a reasonable amount of time.

Finite element dummy models have been more and more widely applied in virtual development of occupant protection systems across the automotive industry due to their predictive capabilities. H350 dyna dummy model [1] is a finite element representation of the Hybrid III male dummy [2], which is designed to represent the average of the United States adult male population. Lower extremity injuries continue to occur in front crash accidents despite increasing improvement of vehicle crashworthiness and occupant restraint system. It is therefore desirable to predict lower tibia injury numbers in front occupant simulations. Though lower tibia loading/index predictions are not studied as much as the FMVSS 208 regulated injury numbers, the tibia indices are injury criteria that need to be assessed during IIHS and Euro NCAP frontal offset occupant simulations. However during front crash simulations, it is very difficult to achieve good correlations or predictions of lower tibia loadings.

It is obvious at this point even to the most casual observer of the automotive industry that efforts to reduce mass throughout the vehicle are at a fervor. The industry is facing its most significant increase in fuel economy standards in its history, and light-weighting the vehicle is a major enabler. Despite the performance and quality of the brake system being intensely related to its mass, it too has not been spared scrutiny. However, like many modern automotive subsystems, it is very complex and mass reduction opportunities that do not sacrifice performance or quality are not always obvious. There are some interesting and sometimes even profound relationships between mass and other vehicle attributes built into brake system design, and making these more visible can enable a better balancing of brake system with the rest of the vehicle design objectives. Examples include - what is the cost, in terms of brake system mass, of added engine power? Of tire and wheel size?

This investigation utilizes energy analysis and statistical methods to optimize step gear automatic transmissions gear selection for fuel consumption. A full factorial matrix of simulations using energy analysis was performed to determine the optimal number of gears and gear ratios that provide the best fuel consumption performance for a particular vehicle - engine application. The full factorial matrix setup as a design of experiment (DOE) was applied to five vehicle applications, each with two engines to examine the potential differences that variations in road load and engine characteristics might have on optimal transmission gearing selection. The transmission gearing options considered in the DOE were number of gears, launch gear ratio and top gear ratio. Final drive ratio was also included due to its global influence on vehicle performance and powertrain operating speeds and torque.

A new approach for modeling and analysis of a transmission and driveline system is proposed. By considering the stiffness, damping and inertias, model equations based on lumped parameters can be created through standard Lagrangian Mechanics techniques. A sensitivity analysis method has then been proposed on the eigenspace of the system characteristic equation to reveal the dynamic nature of a transmission and driveline system. The relative sensitivity calculated can clearly show the vibration modes of the system and the key contributing components. The usefulness of the method is demonstrated through the GM 6-speed RWD transmission by analyzing the dynamic nature of the driveline system. The results can provide a fundamental explanation of the vibration issue experienced and the solution adopted for the transmission.

Spot weld separation in vehicle development stage is one of the critical phenomena in structural analyses regarding quasi-static test condition, like roof strength or seat/belt pull. It directly reduces structural performance by losing connected load path and occasionally introduces tearing on surrounding sheet metals. Traditionally many efforts have been attempted to capture parent metal ductile fracture, but not applied to spot weld separations in automotive FEA simulations. [1,2,3] This paper introduces how to develop FFLD failure criteria from a series of parametric study on ultra high strength sheet steel and deals with failure criteria around spot weld and parent metal. Once the fracture strains for sheet steels are determined, those developed values were applied to traditional spot weld coupon FEA simulations and tests. Full vehicle level roof strength FEA simulations on a typical automotive body structure were performed and verified to the physical tests.

An experimental study was conducted to evaluate the variable amplitude fatigue behavior of a neat polymer (polypropylene impact co-polymer) and a polymer composite made of polybutylene terephthalate (PBT) with 30 wt% short glass fibers. Fatigue tests were conducted on un-notched and notched specimens at room temperatures. Plate-type specimens were prepared in the transverse direction with respect to the injection mold flow direction and a circular hole was drilled in the center of notched specimens. Two-step loadings (high-low and low-high) tests at two damage ratio of 0.2 and 0.5 at stress ratios of R = 0.1 and -1 were conducted to investigate load sequence effects and prediction accuracy of the linear damage rule. Different behaviors were observed for unreinforced and short glass fiber reinforced polymers under the two-step loading tests.

Impact toughness (or resistance to fracture) is a key material property for press hardened steel used in construction of the safety-critical elements of automotive body structures. Prior austenite grain size, as primarily controlled by the incoming microstructure and austenitization process, is a key microstructural feature that influences the impact toughness of press hardened steel. In this paper, a special Charpy V-notch impact test is developed to quantify the impact toughness of press hardened steel sheets with various prior austenite grain sizes, by stacking a number of thin sheets via mechanical riveting. Both the ductile-to-brittle transition temperature and upper shelf energy are analyzed in an effort to establish a correlation between impact toughness and prior austenite grain size. Within tested conditions, impact performance shows only a slight decrease as the prior austenitic grain size increases from 18 to 38 microns.

Aerodynamic vehicle design improvements require flow simulation driven iterative shape changes. The 3-D flow field simulations (CFD analysis) are not explicitly descriptive in providing the direction for aerodynamic shape changes (reducing drag force or increasing the down-force). In recent times, aerodynamic shape optimization using the adjoint method has been gaining more attention in the automotive industry. The traditional DOE (Design of Experiment) optimization method based on the shape parameters requires a large number of CFD flow simulations for obtaining design sensitivities of these shape parameters. The large number of CFD flow simulations can be significantly reduced if the adjoint method is applied. The main purpose of the present study is to demonstrate and validate the adjoint method for vehicle aerodynamic shape improvements.

Adoption of high-pressure common-rail (HPCR) fuel systems, which subject diesel fuels to higher temperatures and pressures, has brought into question the veracity of ASTM International specifications for biodiesel and biodiesel blend oxidation stability, as well as the lack of any stability parameter for diesel fuel. A controlled experiment was developed to investigate the impact of a light-duty diesel HPCR fuel system on the stability of 20% biodiesel (B20) blends under conditions of intermittent use and long-term storage in a relatively hot and dry climate. B20 samples with Rancimat induction periods (IPs) near the current 6.0-hour minimum specification (6.5 hr) and roughly double the ASTM specification (13.5 hr) were prepared from a conventional diesel and a highly unsaturated biodiesel. Four 2011 model year Volkswagen Passats equipped with HPCR fuel injection systems were utilized: one on B0, two on B20-6.5 hr, and one on B20-13.5 hr.

Development of the next generation internal combustion engines and automatic transmissions for automotive applications is a mandatory powertrain engineering activity required now and in the coming years to meet forthcoming global emissions regulations. This paper details a preliminary investigation into possible synergies for fuel consumption reduction considering emerging automotive technologies integrated into the next generation combustion engine and automatic transmission architectures. A range of hypothetical gasoline engines were created and paired with a generalized set of step gear automatic transmissions designed to meet the performance requirements of high volume longitudinal full size truck application. These designs were then run through a design of experiments orthogonal array for prediction of fuel consumption on the WLTP test schedule and stand still acceleration to 100 kph.

Laser welding of dissimilar metals such as Aluminum and Copper, which is required for Li-ion battery joining, is challenging due to the inevitable formation of the brittle and high electrical-resistant intermetallic compounds. Recent research has shown that by using a novel technology, called laser braze-welding, the Al-Cu intermetallics can be minimized to achieve superior mechanical and electrical joint performance. This paper investigates the robustness of the laser braze-welding process. Three product and process categories, i.e. choice of materials, joint configurations, and process conditions, are studied. It is found that in-process effects such as sample cleanness and shielding gas fluctuations have a minor influence on the process robustness. Furthermore, many pre-process effects, e.g. design changes such as multiple layers or anodized base material can be successfully welded by process adaption.

This study concerns the generation of response surfaces for kinematics and injury prediction in pedestrian impact simulations using human body model. A 1000-case DOE (Design of Experiments) study with a Latin Hypercube sampling scheme is conducted using a finite element pedestrian human body model and a simplified parametric vehicle front-end model. The Kriging method is taken as the approach to construct global approximations to system behavior based on results calculated at various points in the design space. Using the response surface models, human lower limb kinematics and injuries, including impact posture, lateral bending angle, ligament elongation and bone fractures, can be quickly assessed when either the structural dimensions or the structural behavior of the vehicle front-end design change. This will aid in vehicle front-end design to enhance protection of pedestrian lower limbs.

An area of brake system design that has remained continually resistant to objective, computer model based predictive design and has instead continued to rely on empirical methods and prior history, is that of sizing the brake pads to insure satisfactory service life of the friction material. Despite advances in CAE tools and methods, the ever-intensifying pressures of shortened vehicle development cycles, and the loss of prototype vehicle properties, there is still considerable effort devoted to vehicle-level testing on public roads using “customer-based” driving cycles to validate brake pad service life. Furthermore, there does not appear to be a firm, objective means of designing the required pad volume into the calipers early on - there is still much reliance on prior experience.

AZ31B Mg sheet is being considered for automotive applications. This study investigates the effect of pre-treatments, such as heat-treatments and surface treatments, on the corrosion performance of AZ31B sheet, with a goal of learning which pre-treatment can improve corrosion resistance of the sheet material in production. It is found that the heat-treatment and oxidation during a warm and hot forming (WHF) process will not deteriorate the corrosion performance of the AZ31B sheet; polishing and acid etching can clean the surface and significantly increase the corrosion resistance, but corrosion can be accelerated by sandblasting which contaminates the surface. The change in corrosion performance can be associated with surface cleaning or contamination of the sheet by these pre-treatments. Furthermore, the influence of a pre-treatment on the uncoated AZ31B sheet may affect its corrosion behavior after coating.

The energy storage system (ESS) is the key enabler to hybrid electric vehicles (HEVs) that offer improved fuel economy and reduced vehicle emissions. The power capability of a battery has significant impact on the fuel economy of HEVs. This paper presents the power capability testing of a lithium-ion battery with a conventional metal oxide cathode using the hardware in the loop (HIL) at a wide range of charge/discharge conditions and at different temperatures. The achieved test results provide critical data of battery power characteristics and effectively accelerate the development of battery power prediction algorithm.

In a math-based control algorithm design, model-based simulation and testing are very important as an integral part of design process. There are many advantages of using modeling and simulation in the algorithm design. In this paper, Algorithm-in-the-Loop and Hardware-in-the-Loop approaches are adopted for a transmission control algorithm development. A practical approach is introduced on how to test the control algorithms with a reliable plant (virtual engine, transmission, and vehicle) model in the closed-loop simulation. In using combination of open-loop and closed-loop simulations, various key behavior test cases are developed and documented for the success of control algorithms development. Secondly, the same test cases are reused and verified against the production codes, which are automatically generated from the math-based control algorithm models.