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This work discusses the development of SAE procedure J2747, “Hydraulic Pump Airborne Noise Bench Test”. This is a test procedure describing a standard method for measuring radiated sound power levels from hydraulic pumps of the type typically used in automotive power steering systems, though it can be extended for use with other types of pumps. This standard was developed by a committee of industry representatives from OEM's, suppliers and NVH testing firms familiar with NVH measurement requirements for automotive hydraulic pumps. Details of the test standard are discussed. The hardware configuration of the test bench and the configuration of the test article are described. Test conditions, data acquisition and post-processing specifics are also included. Contextual information regarding the reasoning and priorities applied by the development committee is provided to further explain the strengths, limitations and intended usage of the test procedure.

In a CAS system, the distance and relative velocity between front and host vehicles are estimated to calculate time-to-collision (TTC). The distance estimates by different methods will certainly include noise which should be removed to ensure the accuracy of TTC calculations. Kalman filter is a good tool to filter such type of noise. Nevertheless, Kalman filter is a model based filter, which means a correct model is important to get the good filtering results. Usually, a vehicle is either moving with a constant velocity (CV) or constant acceleration (CA) maneuvers. This means the distance data between front and host vehicles can be described by either constant velocity or constant acceleration model. In this paper, first, CV and CA models are used to design two Kalman filters and an interacting multiple model (IMM) is used to dynamically combine the outputs from two filters.

The perceived interior noise has been one of the major driving factors in the design of automotive interior assemblies. Buzz, Squeak and Rattle (BSR) issues are one of the major contributors toward the perceived quality in a vehicle. Traditionally BSR issues have been identified and rectified through extensive hardware testing. In order to reduce the product development cycle and minimize the number of costly hardware builds, however, one must rely on engineering analysis and simulation upfront in the design cycle. In this paper, an analytical and experimental study to identify potential BSR locations in a cockpit assembly is presented. The analytical investigation utilizes a novel and practical methodology, implemented in the software tool Nhance.BSR, for identification and ranking of potential BSR issues. The emphasis here is to evaluate the software for the BSR predictions and the identification of modeling issues, rather than to evaluate the cockpit design itself for BSR issues.

A squeal analysis on a front disc brake is presented here utilizing the new complex eigenvalue capability in ABAQUS/Standard. As opposed to the direct matrix input approach that requires users to tailor the friction coupling matrix, this method uses nonlinear static analyses to calculate the friction coupling prior to the complex eigenvalue extraction. As a result, the effect of non-uniform contact pressure and other nonlinear effects are incorporated. Friction damping is used to reduce over-predictions and the velocity dependent friction coefficient is defined to contribute negative damping. Complex eigenvalue predictions of the example cases show very good correlation with test data for a wide range of frequencies. Finally, the participation of rotor tangential modes is also discussed.

This paper reviews the state of the art on analytical design of cockpit modules in two most crucial performance categories: safety and comfort. On safety, applications of finite element analysis (FEA) for achieving robust designs that meet FMVSS 201, 208 and 214 requirements and score top frontal and side NCAP star-ratings are presented. On comfort, focus is placed on Noise, Vibration and Harshness (NVH) performance. Cutting-edge analytical tools for Buzz, Squeak and Rattle (BSR) avoidance and passenger compartment noise reduction are demonstrated. Most of the analytical results shown in this paper are based on the development work of a real-life application program. Correlations between the analytical results and physical test results are included. Examples of Computational Fluid Dynamics (CFD) analysis for climate control are also included. At the end, the road map toward 100 percent virtual prototyping and validation is presented.

This study utilizes complex eigenvalue analysis to investigate the sensitivity of dynamic system stability to the mechanical properties of the friction material. The friction material is modeled as a transverse isotropic material exhibiting different in-plane and out-of-plane moduli. Parametric studies are performed to evaluate system stability under various combinations of these properties. The initial analysis results show good correlation with laboratory testing for both squeal frequency and mode shape. Additional laboratory testing reveals a change in friction material can have a significant effect on the noise performance of a system. Analysis was performed with corresponding friction materials and the results were directionally consistent. This helped to validate the analysis model and establish confidence in the analysis results. In general, for the specific system considered, decreasing both in-plane and out-of-plane moduli encouraged system stability.

The laboratory test method commonly known as “random vibration” is almost always used for Squeak & Rattle testing in today's automotive applications due to its obvious advantages: the convenience in simulating the real road input, the relatively low cost, and efficiency in obtaining the desired test results. Typically, Loudness N10 is used to evaluate the Squeak & Rattle (S&R) performance. However, due to the nature of random distribution of the excitation input, the repeatability of the loudness N10 measurements may vary significantly. This variation imposes a significant challenge when one is searching for a fine design improvement solution in minimizing S&R noise, such as a six-sigma study. This study intends to investigate (1) the range of the variations of random vibration control method as an excitation input with a given PSD, (2) the possibility of using an alternate control method (“time-history replication”) to produce the vibration of a given PSD for a S&R evaluation.

Low frequency drum brake squeal is often very intense and can cause high levels of customer complaints. During a noise event, vehicle framework and suspension components are excited by the brake system and result in a violent event that can be heard and felt during a brake application. This paper illustrates the experimental and analytical studies on a low frequency drum brake squeal problem that caused high warranty cost. First the environmental condition was identified and noise was reproduced. Vehicle tests were performed and operating deflection shapes were acquired. The sensitivity of the lining material to different environmental conditions was investigated. With the use of complex eigenvalue method, models were constructed to obtain further understanding of the phenomena. Finally, the squeal mechanism of a drum brake system is discussed and various solution techniques for low frequency drum brake noise are evaluated.

This paper describes a robust engineering DOE (design of experiment) completed by hydraulic simulation of a Variable Cam Phaser System based on an L4 IC engine. The robust engineering study focused on the high temperature and low speed portions of overall engine operating conditions where the cam phase rates are slow and oscillation is high. The analysis included a preliminary DOE with multiple noise variables used as the control factors in order to quantify and compound the factors into just two noise levels; best and worst conditions. Following the noise DOE, a larger DOE study was completed with 16 control variables including phaser, oil control valve and various engine parameters. It was run at 3 engine rpm (signal levels), 2 noise levels, and was analyzed for 3 responses (advancing rate, retarding rate, and oscillation amplitude while holding an intermediate position). These DOE experiments determined potential gains for each design proposal.