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Over the past decade, the automotive industry has seen a rapid decrease in product development cycle time and an ever increasing need by original equipment manufacturers and their suppliers to differentiate themselves in the marketplace. This differentiation is increasingly accomplished by introducing new technology while continually improving the performance of existing automotive systems. In the area of automotive brake system design, and, in particular, the brake apply subsystem, an increased focus has been placed on the development of electrohydraulic apply systems and brake-by-wire systems to replace traditional pneumatic and hydraulic systems. Nevertheless, the traditional brake apply systems, especially vacuum-based or pneumatic systems, will continue to represent the majority of brake apply system production volume into the foreseeable future, which underscores the need to improve the performance and application of these traditional systems in passenger cars and light-trucks.

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 presents four methodologies for modeling gear mesh excitations in simple and compound planetary gear sets. The gear mesh excitations use simplified representations of the gear mesh contact phenomenon so that they can be implemented in a numerically efficient manner. This allows the gear mesh excitations to be included in transmission system-level, multibody dynamic models for the assessment of operating noise and vibration levels. After presenting the four approaches, a description is made regarding how they have been implemented in software. Finally, example models are used to do a comparison between the methods

A numerical investigation of automobile sunroof buffeting on a prototype sport utility vehicle (SUV) is presented, including experimental validation. Buffeting is an unpleasant low frequency booming caused by flow-excited Helmholtz resonance of the interior cabin. Accurate prediction of this phenomenon requires accounting for the bi-directional coupling between the transient shear layer aerodynamics (vortex shedding) and the acoustic response of the cabin. Numerical simulations were performed using the PowerFLOW code, a CFD/CAA software package from Exa Corporation based on the Lattice Boltzmann Method (LBM). The well established LBM approach provides the time-dependent solution to the compressible Navier-Stokes equations, and directly captures both turbulent and acoustic pressure fluctuations over a wide range of scales given adequate computational grid resolution.

Over the past 20 years, polyvinyl chloride (PVC) has almost replaced metal in stationary glass reveal moldings with dramatic part cost savings on cars and trucks world-wide. The process of assembly is generally simple and convenient but to replace a reveal molding can be difficult. Many times, in order to replace the molding, it may also be necessary to replace or reseal the glass. In short, PVC reveal moldings, relatively inexpensive parts, are very expensive to service. Outside of general assembly and processing issues, there are 5 variables that may cause a failure in the performance of a stationary glass reveal molding. They are as follows: material degradation, crystallization, plasticizer loss, material properties, and molded-in stress. Because of modern standard PVC formulations and the material requirements of most automotive companies, material degradation, crystallization and plasticizer loss do not commonly cause failure. Material properties and molded-in stress do.

This paper examines the aerodynamic forces on the open hood of a stationary vehicle when another large vehicle, such as an 18-wheel semi-truck, passes by at high speed. The problem of semi-truck passing a parked car with hood open is solved as a transient two-vehicle aerodynamics problem with a Dynamic Moving Mesh (DMM) capability in commercial CFD software package FLUENT. To assess the computational feasibility, a simplified compact car / semi-truck geometry and CFD meshes are used in the first trial example. At 70 mph semi-truck speed, the CFD results indicate a peak aerodynamic force level of 20N to 30N on the hood of the car, and the direction of the net forces and moments on the hood change multiple times during the passing event.

Model-based design and development is emerging in the automotive industry, largely revealing its popularity in chassis control systems [1]. Although it is an efficient and accepted design tool for chassis systems, proper processes and strategies need to be in place to ensure the integrity and correctness of the production software. This paper describes software testing strategies for complex chassis control systems in a model-based environment. In detail, it highlights various testing methods for different phases, such as unit testing and integration testing. It will also address issues and challenges that were faced with each method and propose possible solutions.

The value of model-based design has been attempted to be communicated for more than a decade. As methods and tools have appeared and disappeared from a series of different vendors it has become apparent that no single vendor has a solution that meets all users’ needs. Recently standards (UML, MDA, MOF, EMF, etc.) have become a dominant force and an alternative to vendor-specific languages and processes. Where these standards have succeeded and vendors have failed is in the realization that they do not provide the answer, but instead provide the foundation to develop the answer. It is in the utilization of these standards and their capability to be customized that companies have achieved success. Customization has occurred to fit organizations, processes, and architectures that leverage the value of model-driven design.

Managing (minimizing and optimizing) the total mass of a vehicle is recognized as a critical task during the development of a new vehicle, as well as throughout its production lifecycle. This paper summarizes a literature review of, and investigation into, the strategies, methods and best practices for achieving low total mass in new vehicle programs, and/or mass reductions in existing production vehicle programs. Empirical and quantitative data and examples from the automotive manufacturers and suppliers are also provided in support of the material presented.

Adopting robust design principles is a proven methodology for increasing design reliability. General Motors Powertrain (GMPT) has incorporated robust design principles into their Signal Delivery Subsystem (SDSS) development process by moving traditional prototype manufacturing and test functions from hardware to software. This virtual manufacturing technique, where subsystems are built and tested using simulation software, increases the number of possible prototype iterations while simultaneously decreasing the time required to gather statistically meaningful test results. This paper describes how virtual manufacturing was developed using distributed computing.

While the industry has recognized the value of modeling and code generation, the role of verification has taken a limited second tier role. Model Based Testing (MBT) is typically discussed in the context of automation of testing activities to eliminate the burden of generation and execution of tests. Unfortunately, this objective of effort minimization has skewed solutions away from using quality as a guiding metric. Alternatively, we have identified the simple objective of increasing the quality of testing practices and productivity of developers. In the following paper we introduce the integration of traditional software quality practices of functional, unit, and regression testing with the automated, model-driven world. This approach enables a quantitative approach to model driven software quality. The result is a robust technique that enables confident use of model-based development for production applications.

The Advanced Engineering (AE) group within General Motors Powertrain (GMPT) develops next generation engines and transmissions for automotive and marine products. As a research organization, AE needs to prototype design ideas quickly and inexpensively. To this end, AE has embraced model-based development techniques and is currently investigating the benefits of software in-the-loop (SIL) testing. The underlying obstacle faced in developing a practical SIL system lays in the ability to integrate a plant model with sufficient fidelity together with target application software. ChiasTek worked with AE utilizing their CosiMate tool chain to eliminate these barriers and delivered a flexible SIL system simulation solution.

This paper demonstrates the benefit of using simulation and robust optimization for the problem of balancing vehicle noise, vibration, and ride performance over road impacts. The psychophysics associated with perception of vehicle performance on an impact is complex because the occupants encounter both tactile and audible stimuli. Tactile impact vibration has multiple dimensions, such as impact hardness and memory shake. Audible impact sound also affects occupant perception of the vehicle quality. This paper uses multiple approaches to produce the similar, robust, optimized tuning strategies for impact performance. A Design for Six Sigma (DFSS) project was established to help identify a balanced, optimized solution. The CAE simulations were combined with software tools such as iSIGHT and internally developed Kriging software to identify response surfaces and find optimal tuning.

At the early design stage it is easier to achieve impacts on the brake noise. However most noise analyses are applied later in the development stage when the design space is limited and changes are costly. Early noise analysis is seldom applied due to lack of credible inputs for the finite element modeling, the sensitive nature of the noise, and reservations on the noise event screening of the analysis. A high quality brake finite element model of good components’ and system representation is the necessary basis for credible early noise analysis. That usually requires the inputs from existing production hardware. On the other hand in vehicle braking the frequency contents and propensity of many noise cases are sensitive to minor component design modifications, environmental factors and hardware variations in mass production. Screening the noisy modes and their sensitivity levels helps confirm the major noisy event at the early design stage.

The market growth for electric-hybrid passenger vehicles has been very significant and is expected to reach nearly 25% of all vehicles sold in the US by 2015. Hybrid commercial vehicles are also being developed by several OEM's. This paper discusses the progress of Delphi Thermal Systems in developing an integrated electric compressor drive with high cooling capacity (9 kW+), sufficient for large hybrid SUV's and commercial vehicles such as Class 8 tractors with sleeper. An important driver for use of the electric compressor in the hybrid truck application is the reduction of engine idling time while maintaining comfort in the cab or sleeper. Design details of a compact 5 kW SPM motor, its inverter drive, and issues related to its integration into the compressor housing are described. Test results are given confirming excellent performance.

Signal delivery is the means of translating a physical parameter from a sensor measurement to the application software in the electronic controller. Signal delivery is also translating a digital word from the application software to an actuator response. In both cases, there are many transform functions along the path that will introduce noise, error, and non-linearity. This paper will discuss the importance of understanding the error and sensitivity to variation that signal delivery analysis provides. The analysis will direct design change to improve control system robustness as well as decisions for failure events.

This paper outlines a method for computing the transfer functions of structures using their mass loaded responses. According to the method, scaled transfer functions are computed from the response of a structure and without any knowledge of the input forces. The paper outlines the analytical approach, develops the necessary equations for the computation of transfer functions between a mass loading point and other points on a linear dynamic system. A numerical example to show the validity, advantages and limitations of the method is also provided. Currently, the method can be applied to the responses obtained from analytical simulations where it may be necessary to compute coupled response of a simulated dynamic system with other dynamic systems that are not (or cannot be) included in a simulation. It is not uncommon that many dynamic simulations exclude certain coupling effects between the main and the auxiliary systems.

With the revolutionary advances in computing power and software technology, the future trend of integrating design and CFD analysis software package to realize an automated design optimization has been explored in this study. The integrated process of UG, ICEMCFD, and FLUENT was accomplished using iSIGHT for vehicle Aero/Thermal applications. Process integration, CFD solution strategy, optimization algorithm and the practicality for real world problem of this process have been studied, and will be discussed in this paper. As an example of this application, the results of an underhood thermal design will be presented. The advantage of systematical and rapid design exploration is demonstrated by using this integrated process. It also shows the great potential of computer based design automation in vehicle Aero/Thermal development.

Several methods are currently used to enforce motion in different types of noise and vibration models. Experimentally based FRF models often use a matrix inversion technique to enforce motion. In finite element models, the large mass method is one that is very commonly used. A literature review has shown few guidelines for determining the size of these large masses. In this paper, the relationship between the matrix inversion technique and the large mass method is derived. From this relationship, conditions necessary for these large mass FEM models to converge to the same answers as the matrix inversion technique are derived. These conditions are then used to develop a criterion for determining a smallest possible large mass. Results from a simple model are presented to demonstrate the criterion.

Recently published SAE Recommended Practice J2562 - SAE Biaxial Wheel Test standardized the terminology, equipment, and test procedure for the biaxial wheel test. This test was originally presented by Fraunhofer Institut Betriebsfestigkeit - LBF (Fraunhofer Institute for Structural Durability) in SAE paper 830135 “Automotive Wheels, Method and Procedure for Optimal Design and Testing”. The first release of SAE J2562 included a generic, scalable load file applicable to wheels designed for five to eight passenger vehicles with capacity to carry a proportional amount of luggage or ballast. Future releases of SAE J2562 would include two additional load files; one applicable to light trucks that have substantial cargo capacity and one for sports cars typically limited to two passengers and marginal luggage. This report details the process used to develop the SAE Biaxial Wheel Test Load File for passenger vehicles.