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For a numerical model of vibro-acoustic coupling analysis, such as a vehicle noise and vibration, both structural and acoustical dynamic characteristics are necessary to replicate the physical phenomenon. The accuracy of the analysis is not enough for substituting a prototype phase with a digital phase in the product development phases. One of the reasons is the difficulty of addressing the interior acoustical characteristics due to the complexity of the acoustical transfer paths, which are a duct and a small hole of trim parts in a vehicle. Those complex features affect on the nodal locations and the body coupling surface of acoustic mode shapes. In order to improve the accuracy of the analysis, the physical mechanisms of those features need to be extracted from experimental testing.

The use of CAE software in developing plastic components has advanced rapidly in recent years. This progress has been supported by the development of practical analytical tools, based on the finite element and boundary element methods, and on the dramatic improvements seen in computer performance. Following the introduction of a flow analysis program in 1982, Nissan has developed and implemented advanced programs for use in developing plastic components and has integrated the programs into a unified in-house system. This system is being utilized at the design and manufacturing stages of interior and exterior trim parts and has produced concrete results in different phases of component development. Work is now proceeding on the development of a system that can simultaneously analyze both the component performance and the factors that need to be considered in the manufacturing process.

Since interior noise has a strong effect on vehicle salability, it is particularly important to be able to estimate noise levels accurately by means of simulation at the design stage. The use of sensitivity analysis makes it easy to determine how the analytical model should be modified or the structure optimized for the purpose of reducting vibration and noise of the structural-acoustic systems. The present work focused on a structural-acoustic coupling problem. As the coefficient matrices of a coupled structural-acoustic system are not symmetrical, the conventional orthogonality conditions obtained in structural dynamics generally do not hold true for the coupled system. To overcome this problem, the orthogonality and normalization conditions of a coupled system were derived by us. In this paper, our sensitivity analysis methods are applied to an interior noise problem of a cabin model.

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.

Achieving a multi-cylinder engine with excellent noise/vibration character sties and low friction at the main bearings requires an optimal design not only for the crankshaft construction but also for the bearing support system of the cylinder block. To accomplish that, it is necessary to understand crankshaft system behavior and the bearing load distribution for each of the main bearings. Crankshaft system behavior has traditionally been evaluated experimentally because of the difficulty in performing calculations to predict resonance behavior over the entire engine speed range. A coupled crankshaft-block analysis method has been developed to calculate crankshaft system behavior by treating vibration and lubrication in a systematic manner. This method has the feature that the coupled behavior of the crankshaft and the cylinder block is analyzed by means of main bearing lubrication calculations. This paper presents the results obtained with this method.

To address the growing need for detailed chemistry in engine simulations, new software tools and validated data sets are being developed under an industry-funded consortium involving members from the automotive and fuels industry. The results described here include systematic comparison and validation of detailed chemistry models using a wide range of fundamental experimental data, and the development of software tools that support the use of detailed mechanisms in engineering simulations. Such tools include the automated reduction of reaction mechanisms for targeted simulation conditions. Selected results are presented and discussed.

Engines that not only produce less noise but also provide good sound quality have been in increasing demand recently. Discomforting noise can sometimes be heard, however, during acceleration as the engine reaches higher levels of power and speed. This paper presents the results of a study into the bending vibration of the crankshaft-flywheel system, which clarify the mechanism producing discomforting noise during acceleration. Based on that study, a flexible flywheel has been developed which effectively reduces crankshaft bending vibration that is closely related to the frequency range of the discomforting noise. As a result, acceleration sound quality is greatly improved.

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.

This paper presents the hybrid technique application in identifying the noise transfer paths and the force transmissibility between the interfaces of the different components in the vehicle. It is the stiffness based formulation and is being applied for the low to mid frequency range for the vibration and structure borne noise. The frequency response functions such as dynamic compliance, mobility, inertance, and acoustic sensitivity, employed in the hybrid method, can either be from the test data or finite element solution or both. The Source-Path-Receiver concept is used. The sources can be from the road surface, engine, transmission, transfer case, prop-shaft, differential, rotating components, chain drives, pumps, etc., and the receiver can be driver/passenger ears, steering column, seats, etc.

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.

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.

Recently, it has been very important to reduce the noise, especially the Squeak and Rattle noise, for improving customer appeal of passenger vehicles. The Squeak and Rattle noise occurring inside the car cabin during vehicle operation is an especially large problem. This paper describes a newly developed measurement technology that uses the developed signal processing using the Beam-forming method and vibration sensor to identify the Squeak and Rattle noise sources, making it possible to determine effective countermeasures quickly. This new technology is used to identify all Squeak and Rattle noises at a time among many different noises, for example Wind noise, Engine noise and Road noise occurring during vehicle operation, and is expected to shorten substantially the time needed for noise analysis and contribute to quality improvements.

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.

A seat vibration prediction technique using a substructure synthesis method was developed for use in ride comfort evaluations. The human body was modeled as a vibration transfer matrix using the mean apparent mass of human subjects, based on data measured in advance. Seat vibration characteristics were measured with rigid masses on the seat. The measured data and vibration transfer matrix of the human body were synthesized using a substructure synthesis method, to predict vibration of the seat cushion and backrest in an occupant-loaded condition without actually using human subjects. Results showed that seat vibration predicted with this method was very similar to, and more repeatable than, that obtained experimentally with human subjects.

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.