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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.

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.

New seal cross-section development is a very tedious and time consuming process if conventional analysis methods are used, as it is very difficult to predict the dimensions of the seal that will satisfy the sealing performance targets. In this study, a generic cross-section is defined and the design constraints are specified. Isight then runs the FEA model, utilizing a custom python script for post-processing. Isight then updates the dimensions of the seal and continues running analyses. Isight was run using two different design exploration techniques. The first was a design of experiments (DOE) to discover how the seal’s response varies with its dimensions. Then, after the analyst examined the results, Isight was run in optimization mode focusing on feasible design areas as determined from the DOE. Thus, after the initial model setup, the user can run the analyses in the background and only needs to interact with the program after Isight has determined a list of feasible designs.

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.

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.

An aspect of high performance brake design that has remained strikingly empirical is that of determining the correct sizing of the brake pad - in terms of both area and volume - to match well with a high performance vehicle application. Too small of a pad risks issues with fade and wear life on the track, and too large has significant penalties in cost, mass, and packaging space of the caliper, along with difficulties in maintaining adequate caliper stiffness and its impact on pedal feel and response time. As most who have spent time around high performance brakes can attest to, there methods for determining minimum brake pad area, usually related in some form or another to the peak power the brake must absorb (functions of vehicle mass and top speed are common). However, the basis for these metrics are often lost (or closely guarded), and provide very little guidance for the effects of the final design (pad area) deviating from the recommended value.

The headliner system in a vehicle is an important element in vehicle noise control. In order to predict the performance of the headliner, it is necessary to develop an understanding of the substrate performance, the effect of air gaps, and the contribution from any acoustic pads in the system. Current Statistical Energy Analysis (SEA) models for predicting absorption performance of acoustic absorbers are based on material Biot properties. However, the resources for material Biot property testing are limited and cost is high. In this paper, modeling parameters for the headliner substrate are identified from a set of standard absorption measurements on substrates, using curve fitting and optimization techniques. The parameters are then used together with thickness/design information in a SEA model to predict the vehicle headliner system absorption performance.

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.

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.

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.

This paper presents the most recent advancement in the vehicle development process using the one-step or auto Transfer Path Analysis (TPA) in conjunction with the superelement, component mode synthesis, and automated multi-level substructuring techniques. The goal is to identify the possible ways of energy transfer from the various sources of excitation through numerous interfaces to given target locations. The full vehicle model, consists of superelements, has been validated with the detailed system model for all loadcases. The forces/loads can be from rotating components, powertrain, transfer case, chain drives, pumps, prop-shaft, differential, tire-wheel unbalance, road input, etc., and the receiver can be at driver/passenger ears, steering column/wheel, seats, etc. The traditional TPA involves two solver runs, and can be fairly complex to setup in order to ensure that the results from the two runs are consistent with subcases properly labeled as input to the TPA utility.

This investigation utilizes a DFSS analysis approach to determine automatic transmission gear content required to minimize fuel consumption for various powertrain - vehicle systems. L18 and L27 inner arrays with automatic transmission design and shift pattern constraint parameters were varied to determine their relative influence on fuel consumption. An outer noise array consisting of two vehicles with various engines, final drive ratios and legislated emissions test cycles was used to make a robust transmission selection based on minimizing fuel consumption. The full details of the DFSS analysis method and assumptions are presented along with a detailed examination of the results. With respect to transmission design parameters, parasitic spinloss and gear mesh efficiency were found to be most important followed by the number of gears. The DFSS analysis further revealed that unique transmission design formulations are potentially required for widely varying engines.

With the ever increasing pressure to improve the fuel economy of vehicles, there has been a corresponding interest in reducing the mass and size of vehicles. While mass is easily quantifiable, vehicle size, particularly the notion of “interior space” as perceived by the customer, is not. This paper explores different ways in which vehicle spaciousness can be quantified and explores new metrics based on customer verbatims. A novel ‘spaciousness calculator’ combines individual metrics to provide a singular holistic rating for spaciousness, useful during vehicle development. Beyond spaciousness, the paper discusses techniques to quantify the ‘packaging efficiency’ of a vehicle; this allows engineers to maximize the interior space for a given exterior size.

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.

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.

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.

A hot and cold water mixing process with a steam condenser and a chilled water heat exchanger is set up for an engine EGR fouling test. The test rig has water recycled in the loop of a pump, heat exchangers, a three-way mixing valve, and a test EGR unit. The target unit temperature is controlled by a heating, cooling and mixing process with individual valves regulating the flow-rate of saturated steam, chilled water and mixing ratio. The challenges in control design are the dead-time, interaction, nonlinearity and multivariable characteristics of heat exchangers, plus the flow recycle in the system. A systems method is applied to extract a simple linear model for control design. The method avoids the nonlinearity and interaction among different temperatures at inlet, outlet and flow-rate. The test data proves the effectiveness of systems analysis and modeling methodology. As a result, the first-order linear model facilitates the controller design.

Corrosion inhibitors (CIs) have been used for years to protect the supply and distribution systems used for transportation of fuel from refineries. They are also used to buffer the potential organic acids present in an ethanol blended fuel to enhance storage stability. The impact of the types of inhibitors on spark-ignition engine fuel systems, specifically intake valve deposits, is known and presented in open literature. However, the relationship of the corrosion inhibitors to the powertrain intake valve deposit performance is not understood. This paper has two purposes: to present and discuss a survey of corrosion inhibitors and how they vary in concentration in the final blended fuel, specifically E85 (Ethanol Fuel Blends); and to show how variation in concentration of components of CIs and detergents impact intake valve deposit formation.

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).