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Springback is a serious problem in sheet metal stamping. It measures the difference between the final shape of the part and the shape of the forming die. Sheet metal forming simulation has made significant progress in predicting springback and several computer simulation codes are commercially available to predict and compensate for it in tool design. The accurate prediction of springback is important and there is a need to validate and verify those predictions with experimental results. Current validation techniques lack standardized procedures, require measurement fixtures that may impose unrealistic restraint on the part, require profiling equipment such as CMM or laser scanning and for the most part produce small springback which reduces measurement accuracy and increases experimental error. A benchmark test has been developed which addresses all these concerns and compares springback predictions by various numerical simulation codes with each other and with experimental results.

A study was conducted using Ford's nine standard CFD calibration models as described in SAE paper 940323. The models are identical from the B-pillar forward but have different back end configurations. These models were created for the purpose of evaluating the effect of back end geometry variations on aerodynamic lift and drag. Detailed experimental data is available for each model in the form of surface pressure data, surface flow visualization, and wake flow field measurements in addition to aerodynamic lift and drag values. This data is extremely useful in analyzing the accuracy of the numerical simulations. The objective of this study was to determine the capability of a digital physics based commercial CFD code, PowerFLOW ® to accurately simulate the physics of the flow field around the car-like benchmark shapes.

Software development for automotive application requires several iterations in order to tune parameters and strategy logic to operate accordantly with optimal performance. Thus, in this paper we present an optimizer method and tool used to tune calibration parameters related to torque estimation for a hybrid automatic transmission application. This optimizer aims to minimize the time invested during the software calibration and software development phases that could take significant time in order to cover the different driving conditions under which a hybrid automatic transmission can operate. For this reason, an optimization function based on the Nelder-Mead simplex algorithm using Matlab software helps to find optimized calibration values based on a cost function (square sum error minimization).

There are several reasons why it can be daunting to apply Six Sigma to product creation. Foremost among them, the functional performance of new technologies is unknown prior to starting a project. Although, Design For Six Sigma (DFSS) was developed to overcome this difficulty, a lack of applicable in-class case studies makes it challenging to train the product creation community. The current paper describes an in-class project which illustrates how Six Sigma is applied to a simulated product creation environment. A toy construction set (TCS) project is used to instruct students how to meet customer expectations without violating cost, packaging volume and design-complexity constraints.

Designing a durability test for an automatic transmission that appropriately reflects customer usage during the lifetime of the vehicle is a formidable task; while the transmission and its components must survive severe usage, overdesigning components leads to unnecessary weight, increased fuel consumption and increased emissions. Damage to transmission components is a function of many parameters including customer driving habits and vehicle and transmission characteristics such as weight, powertrain calibration, and gear ratios. Additionally, in some cases durability tests are required to verify only a subset of the total parameter space, for example, verifying only component modifications. Lastly, the ideal durability test is designed to impose the worst case loading conditions for the maximum number of internal components, be as short as practicable to reduce testing time, with minimal variability between tests in order to optimize test equipment and personnel resources.

The Snook tables (Liberty Mutual Tables) are a collection of data sets compiled from studies based on a psychophysical approach to material-handling tasks. These tables are used to determine safe loads for lifting, lowering, carrying pulling, and pushing. The tables take into account different population percentiles, gender, and frequency of activity. However, while using these tables to analyze a work place, Ergonomists often have to select from discrete data points closest to the actual work place parameters thereby reducing accuracy of results. To compound the problem further, multiple interrelated variables are involved, making it difficult to analyze parameters intuitively. For example, it can be difficult to answer questions such as, does reducing the lifting height lower the recommended lifting weight, if the lifting distance is increased? To resolve such issues, this paper presents a new methodology for implementing the Snook tables using multi variable regression.

SiC devices have inherent fast switching capabilities due to their superior material properties, and are considered potential candidates to replace Si devices for traction inverters in electrified vehicles in future. However, due to the comparatively low gate threshold voltage, SiC devices may encounter oscillatory false triggering especially during fast switching. This paper analyzed the causes of false triggering, and also studied the impact of a critical parasitic parameter - common source inductance. It is shown that crosstalk is the main cause for the false triggering in the case and some positive common source inductance help to mitigate the crosstalk issue. A packaging layout method is proposed to create the positive common source inductance through layout of control terminals / busbars, and/or the use of control terminal bonded wires at different height.

Understanding the variation in the deployment times for crash sensor systems is important to ensure robust performance of a crash sensor system. Increases in both the numbers of crash modes and deployable devices have reduced the margins for the decisions about when to deploy any given device. Currently, the industry practice is to run a sweep over the potential sources of variation, recording the minimum and maximum deployment time. Questions such as: “How often do the extremes occur?” or “Are there multiple peaks in the deployment time?” can not be answered. This work uses numerical analysis methods to build on the current sweep methodology to obtain information on the distribution of the deployment times so that questions such as these can be answered when evaluating sensor calibrations. The end result is better informed engineering decisions during the calibration development.

To address the need of increasing fuel economy requirements, automotive Original Equipment Manufacturers (OEMs) are increasing the number of turbocharged engines in their powertrain line-ups. The turbine-driven technology uses a forced induction device, which increases engine performance by increasing the density of the air charge being drawn into the cylinder. Denser air allows more fuel to be introduced into the combustion chamber, thus increasing engine performance. During the inlet air compression process, the air is heated to temperatures that can result in pre-ignition resulting and reduced engine functionality. The introduction of the charge air cooler (CAC) is therefore, necessary to extract heat created during the compression process. The present research describes the physics and develops the optimized simulation method that defines the process and gives insight into the development of CACs.

Static seating bucks have long been used as the only means to subjectively appraise the vehicle interior packages in the vehicle development process. The appraisal results have traditionally been communicated back to the requesting engineers either orally or in a written format. Any design changes have to be made separately after the appraisal is completed. Further, static seating bucks lack the flexibility to accommodate design iterations during the evolution of a vehicle program. The challenge has always been on how to build a seating buck quickly enough to support the changing needs of vehicle programs, especially in the early vehicle development phases. There is always a disconnect between what the seating buck represents and what is in the latest design (CAD), since it takes weeks or months to build a seating buck and by the time it is built the design has already been evolved. There is also no direct feedback from seating buck appraisal to the design in CAD.

Good air/fuel ratio (A/F) control is essential to high quality combustion performance, drivability and emissions in internal combustion engine powered vehicles. Cold start and transient fuel wall wetting effects cause significant A/F control challenges in port fuel injected (PFI) engines. Transient fuel compensation (TFC) strategies are used to help control the A/F during cold starts and transient load and RPM conditions for good vehicle performance, but developing optimum TFC strategies and calibrations in a vehicle with many competing effects is very difficult. Thus, simplified transient tests such as fuel or throttle perturbation tests are often used to develop and validate new strategies or calibrations for use in vehicle. This paper will illustrate the use of a validated physical model to analytically assess the value of fuel and throttle perturbation tests for developing a TFC calibration for vehicle use.

This paper presents the development and applications of engine friction algorithms to quickly estimate performance, optimum geometry of critical engine components, and packaging for rapid engine concept assessments. The development and implementation of some knowledge-based design rules will also be presented to quickly estimate the critical geometry of engine components and component weight such as valve sizing, piston weight, crankshaft geometry, etc. Some examples of powertrain concept design, such as the estimation of friction and packaging will be presented. The simulation results of the friction algorithms will be compared to some of available experimental data and also other friction estimation methods.

An assessment tool was developed for rollover CAE signals evaluation to assess primarily the qualities of CAE generated sensor waveforms. This is a key tool to be used to assess CAE results as to whether they can be used for algorithm calibration and identify areas for further improvement of sensor. Currently, the method is developed using error estimates on mean, peak and standard deviation. More metrics, if necessary, can be added to the assessment tool in the future. This method has been applied to various simulated signals for laboratory-based rollover test modes with rigid-body-based MADYDO models.

Turbocharger compressors are susceptible to surge – the instability phenomena that impose limitations on the operation of turbocharged engines because of undesired noise, engine torque capability constraints, and hardware strain. Turbocharged engines are typically equipped with a binary compressor recirculation valve (CRV) whose primary function is to prevent compressor surge. Calibration of the associated control strategy requires in-vehicle tests and usually employs subjective criteria. This work aims to reduce the calibration effort for the strategy by developing a test procedure and data processing algorithms. An automated calibration for CRV control is developed that will generate a baseline calibration that avoids surge events. The effort to obtain the baseline calibration, which can be further fine-tuned, is thereby significantly reduced.

The FMEA and DV&PV process of developing automotive products requires identifying and repeatedly testing critical vehicle attributes and their response to noise factors that may impair vehicle function. Ford has developed a new automated scripting tool to streamline in-vehicle robustness testing and produce more accurate and repeatable results. Similar noise factors identified during the FMEA process are grouped together, condensed, and scripts are developed to simulate these noise factors using calibration parameters and vehicle controls. The automated testing tool uses the API of a calibration software tool and a graphical scripting interface to consistently simulate driver inputs with greater precision than a human calibrator and enable more sophisticated controls, which would have previously required experimental software builds. The noise factor scripts are executed with minimal intervention from a human operator, and the collected data is analyzed to determine robustness.

The automotive refrigerant systems can occasionally exhibit a transient hoot/whistle type noise under certain operating conditions. High pressure/velocity refrigerant flow through an evaporator core can readily excite the inherent acoustical and/or structural modes, resulting in audible transient tones. This condition if present can be experienced while driving away from a short stop and can last 2 to 10 seconds. The ambient conditions suitable for creating this noise are - moderate/high air-conditioning (A/C) load during days at 85-95° F temperatures with high humidity. Possible noise generating mechanisms have been discussed in earlier publications and our findings during this study indicate that they are excited by the high velocity superheated refrigerant vapor flow through the evaporator core plates. Examples of this transient noise and its spectral characteristics are presented to characterize this refrigerant system induced issue.

This paper focuses on the development of a framework of nonlinear finite element model validation for vehicle crash simulation. Integrated computational and test-based methods were discussed for validating computational models under physical, informational and model uncertaintes. Several methods were investigated to quantify transient time-domain data (functional data). The concept of correlation index was proposed to determine the degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. The methodologies developed in this paper can also be used for CAE model updating, parameter tuning, and model calibration.

Control of vehicle powertrain thermal management systems is becoming more challenging as the number of components is growing, and as a result, advanced control methods are being investigated. Model predictive control (MPC) is particularly interesting in this application because it provides a suitable framework to manage actuator and temperature constraints, and can potentially leverage preview information if available in the future. In previous SAE publications (2015-01-0336 and 2016-01-0215), a robust MPC control formulation was proposed, and both simulation and powertrain thermal lab test results were provided. In this work, we discuss the controller deployment in a vehicle; where controller validation is done through road driving and on a wind tunnel chassis dynamometer. This paper discusses challenges of linear MPC implementation related to nonlinearities in this over-actuated thermal system.

A typical automotive catalytic converter is constructed with a ceramic substrate and a steel shell. Due to a mismatch in coefficients of thermal expansion, the steel shell will expand away from the ceramic substrate at high temperatures. The gap between the substrate and shell is usually filled with a fiber composite material referred to as “mat.” Mat materials are compressed during assembly and must maintain an adequate pressure around the substrate under extreme temperature conditions. The container deformation measurement procedure is used to determine catalytic converter shell expansion during and after a period of hot catalytic converter operation. This procedure is useful in determining the potential physical durability of a catalytic converter system, and involves measuring converter shell expansion as a function of inlet temperature. A post-test dimensional measurement is used to determine permanent container deformation.

Ultrasonic fatigue tests (testing frequency around 20kHz) have been conducted on A356 aluminum alloys with different copper contents and AS7GU aluminum alloy. Tests were performed in dry air and submerged in water conditions. The effect of copper content was investigated and it was concluded that copper content plays an important role influencing the humidity effect on A356 aluminum alloy ultrasonic fatigue lives. Also, for the same copper content, copper in solute solution or in precipitate have different humidity sensitivities.