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An evaluation methodology has been developed for assessing the suitability of R-1234yf in vehicles. This relates primarily to evaluating the flammability of R-1234yf in the engine compartment during a frontal collision. This paper will discuss the process followed in the methodology, the technical rationale for this process, and the results of the analysis. The specific types of analysis included in the methodology are: exhaust-system thermal characterization, computer simulated crash tests, actual crash tests, teardown and examination of crashed parts, and releases of refrigerant onto hot exhaust manifolds. Each type of analysis was logically ordered and combined to produce a comprehensive evaluation methodology. This methodology has been applied and demonstrates that R-1234yf is difficult to ignite when factors that occur in frontal crashes are simultaneously considered.

A GT-Power Fast Run Model simplified from detail model for HIL is verified with a bench test using the dSPACE Simulator. Firstly, the conversion process from a detailed model to FRM model is briefly described. Then, the spark timing, fuel pulse with control for FAR, and torque level control are developed for proof of concept. Moreover a series of FRM/Simulink co-simulation and HIL tests are conducted. In the summary, the test results are presented and compared with GT detailed model simulations. The test results show that the FRM/dSPACE HIL stays consistent in most variables of interest under 0.7-0.9 real-time factor condition between 1000 - 5000 RPM. The same steady-state can be reached by RCP controllers or with GT-Power internal controllers. The transient states are close using different control algorithm. The main purpose of HIL application is achieved, despite inconsistencies in performance data like fuel consumption.

A rough road ride assessment provides an insightful evaluation of vehicle responses beyond the frequency range of suspension or steering modes. This is when body structure influence on the vehicle performance can be detected by vehicle occupants. In this paper, a rough road is used to evaluate vehicle ride performance and multi-body simulation (MBS) models are developed along with finite-element (FE) representations of the vehicle body and structure. To produce high fidelity simulation results in the frequency range of interest, various vehicle subsystem modeling contents are examined. A case study of a vehicle model with two different structures is provided. Time histories and frequency based analyses are used to obtain insights into the effects of body structure on vehicle responses. Finally, two metrics (‘Isolation’ and ‘Shake’) are used to distinguish the vehicle ride performance.

AUTOSAR(AUTomotive Open System ARchitecture) establishes an industry standard for OEMs and the supply chain to manage growing complexity to the automotive electronics domain. Increased focus on software based features will prove to be a key differentiator between vehicle platforms. AUTOSAR serves to standardize automotive serial data communication protocols, interaction with respect to hardware peripherals within an ECU and allow ECU implementer to focus on development of unique customer focused features that distinguish product offerings. Adoption strategy and impact assessment associated with leveraging AUTOSAR for an E/E Architecture and the potential challenges that need to be considered will be described in this publication. This publication will also illustrate development strategies that need to be considered w.r.t deploying AUTOSAR like data exchange, consistency to BSW software implementation, MCAL drivers etc.

In automotive noise control, the hood liner is an important acoustic part for mitigating engine noise. The random incidence absorption coefficient is used to quantify the component level acoustic performance. Generally, air gaps, type of substrate materials, density of the substrate materials and Air Flow Resistivity (AFR) of the cover scrim are the dominant control factors in the sound absorption performance. This paper describes a systematic experimental investigation of how these control factors affect flat sample performance. The first stage of this study is full factorial measurement based on current available solutions from sound absorber suppliers. The acoustic absorption of different hood liner constructions, with variations in materials, density, air gaps, and scrims was measured.

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.

In the early vehicle design stage math model, subsystems such as dummies, airbags and interior trims are generally not considered for structural evaluation. The objective of this study is to evaluate the B-pillar intrusion and velocity sensitivity in a side impact load case with respect to the dummies, airbags and interior trim. In this study four different vehicles were used to understand the B-pillar intrusion and velocity sensitivity trends. US NCAP lateral impact load case is used in this study. Five side impact load case analyses iterations, with different combinations of subsystems, were completed. Dummy inertia and interior trims play an important role for B-Pillar intrusion and velocity in side impact load case (USLINCAP). If the dummy and interior trim is not well defined in the CAE model, higher B-pillar intrusion and velocity will be predicted. This could vary from 10 to 25 %.

The automotive industry is one of the most competitive enterprises in the world. Customers face an ever-expanding number of entries in each market segment vying for their business. Sales price, brand image, marketing, etc. all play a role in purchase decisions, but the factor distinguishing products that consistently perform in the market place is the ability to satisfy the customer. Steering character plays a critical role in the customer driving experience and can be one of the most heavily debated topics during a new vehicle program. The proliferation of EPS steering systems now allows engineers to calibrate steering feel to almost any desired specification. This raises a key question: What subjective & objective characteristics satisfy customers in a particular market segment?

Automotive interior design optimization must balance the design of the vehicle seat and occupant space for safety, comfort and aesthetics with the accommodation of add-on restraint products such as child restraint systems (CRS). It is important to understand the range of CRS dimensions so that this balance can be successfully negotiated. CRS design is constantly changing. In particular, the introduction of side impact protection for CRS as well as emphasis on ease of CRS installation has likely changed key design points of many child restraints. This ever-changing target creates a challenge for vehicle manufacturers to assure their vehicle seats and occupant spaces are compatible with the range of CRS on the market. To date, there is no accepted method for quantifying the geometry of child seats such that new designs can be catalogued in a simple, straightforward way.

Mahalanobis Distance (MD) is gaining momentum in many fields where classification, statistical pattern recognition, and forecasting are primary focus. It is a multivariate method and considers correlation relationships among parameters for computing generalized distance measure to separate groups or populations. MD is a useful statistic in multivariate analysis to test that an observed random sample is from a multivariate normal distribution. This capability alone enables engineers to determine if an observed sample is an outlier (defect) that falls outside the constructed (good) multivariate normal distribution. In Mahalanobis-Taguchi System (MTS), MD is suitably scaled and used as a measure of severity in abnormality assessment. It is obvious that computed MD depends on values of parameters observed on a random sample. All parameters may not equally impact MD. MD could be highly sensitive with respect to some parameters and less sensitive to some other parameters.

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.

This paper compares the material consumption and fire patterns which developed on four nearly identical compact sedans when each was burned for exactly the same amount of time, but with different wind speed and direction during the burns. This paper will also compare the effects of environmental exposure to the fire patterns on the vehicles. The burn demonstrations were completed at an outdoor facility in southeast Michigan on four late model compact sedans. The wind direction was controlled by placing the subject vehicle with either the front facing into the wind, or rear facing into the wind. Two of the burns were conducted when the average observed wind speed was 5-6kph and two of the burns were conducted at an average observed wind speed of 19kph.

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.

Development of the software using fixed-point arithmetic is known to be tedious and error-prone. Difficulty of selecting the correct data type can outwear software developers. The common retreats often sought after include manual calculation of the approximate ranges, exhaustive simulations with extreme input values and conservative development approach by using excessive word length. The first two retreats - manual calculation and exhaustive simulations - increase the software development time, and the third retreat - conservative development - leads to the excessive memory (RAM and ROM) utilization by the software. The model-based development environment such as the Simulink has graphical nature to the software with flow of data defined by connecting signal lines. The model-based software therefore gives an opportunity to trace signal flow in the software. Input-tracing method is presented to trace the flow of the input signals of the user selected block in the software model.

Classic, hot-spot induced pre-ignition is a phenomenon that has been observed in gasoline spark ignited engines over the past 60-70 years. With the development of turbocharged, direct-injected (DI) gasoline engines, a new pre-ignition phenomenon occurring at low engine speeds and high loads has been encountered. Termed Stochastic Pre-ignition (SPI), it has become a significant issue to address in allowing for the full potential of gasoline turbo DI technology to improve powertrain efficiency. Many researchers are studying all aspects of the causes of Stochastic Pre-ignition, including causes by oil, fuel and engine hardware systems. The focus of this specific research was to study the relationship of fuel octane and volatility to Stochastic Pre-ignition behavior utilizing a GM 2.0L Gasoline Turbocharged DI engine (LHU).

Today's sophisticated state-of-the-art powertrains with various intelligent control units (xCU) need to be calibrated and tested stand-alone as well as in interaction. Today the majority of this work is still carried out with prototype vehicles on test tracks. Moving prototype vehicle tests from the road into the lab is key in achieving shorter development times and saving development cost. This kind of frontloading requires a modular and powerful simulation of all vehicle components, test track, and driver in steady state and dynamic operation. The described HIL (Hardware In the Loop) high performance driveline dyno test bed uses driveline components and models from the engine all the way to the wheel ends. The test cell was built to do real time vehicle maneuvers and NVH testing. This test setup can emulate any road surface and grade and vehicle inertia including wheels and engine as close to reality as possible.

Oil canning and initial stiffness of the automotive roofs and panels are considered to be sensitive customer ‘perceived quality’ issues. In an effort to develop more accurate objective requirements, respective simulation methods are continuously being developed throughout automotive industries. This paper discusses a latest development on oil canning predictions using LS-DYNA® Implicit, including BNDOUT request, MORTAR contact option and with the stamping process involved, which resulted in excellent correlations especially when it comes to measurements at immediate locations to the feature lines of the vehicle outer panels. Furthermore, in pursuit of light-weighting vehicles with thinner roofs, a new CAE method was recently developed to simulate severe noise conditions exhibited on some of developmental properties while going through a car wash.

This paper presents an overview of a four-year project focused on development of an integrated computational materials engineering (ICME) toolset for third generation advanced high-strength steels (3GAHSS). Following a brief look at ICME as an emerging discipline within the Materials Genome Initiative, technical tasks in the ICME project will be discussed. Specific aims of the individual tasks are multi-scale, microstructure-based material model development using state-of-the-art computational and experimental techniques, forming, toolset assembly, design optimization, integration and technical cost modeling. The integrated approach is initially illustrated using a 980MPa grade transformation induced plasticity (TRIP) steel, subject to a two-step quenching and partitioning (Q&P) heat treatment, as an example.

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.

In the vehicle development process, one important step is to set a component performance target from the vehicle level performance. Conventional barrier-decoupler dash mats and floor trim underlayment systems typically provide sound transmission loss (STL) with minimal absorption. Thus the performance of such components can be relatively easily specified as either STL or Insertion Loss. Lightweight dissipative or multi-layered acoustic materials provide both STL and significant absorption. The net performance is a combination of two parameters instead of one. The target for such components needs to account for this combined effect, however different suppliers use unique formulations and manufacturing methods, so it is difficult and time consuming to judge one formulation against another. In this paper, a unique process is presented to set a component target as a combined effect of STL and absorption.