Search Results

In recent years, Nearfield Acoustical Holography (NAH) has been used to identify stationary vehicle exterior noise sources. However that application has usually been limited to individual components. Since powertrain noise sources are hidden within the engine compartment, it is difficult to use NAH to identify those sources and the associated partial field that combine to create the complete exterior noise field of a motor vehicle. Integrated Nearfield Acoustical Holography (INAH) has been developed to address these concerns: it is described here. The procedure entails sensing the sources inside the engine compartment by using an array of reference microphones, and then calculating the associated partial radiation fields by using NAH. In the second part of this paper, the use of farfield arrays is considered. Several array techniques have previously been applied to identify noise sources on moving vehicles.

In experimental work, it is well known that measured values are not exact. Statistical treatment of uncertainty in measured values is common. The propagation of uncertainty in measured values into calculated values is examined. This technique of uncertainty analysis presented provides a rigorous mathematical technique for the analysis of uncertainty propagation from experimentally measured values into calculated results. The method of uncertainty analysis is introduced in general and an application to the momentum equation is examined to demonstrate the technique. The example presented demonstrates the effectiveness of the technique by demonstrating the growth of uncertainty in the calculated results around a singularity in the equations.

China has become the world’s largest vehicle market in terms of sales volume. Automobiles sales keep growing in recent years despite the declining economic growth rate. Due to the increasing attention given to the environmental impact, more stringent emission regulations are being drafted to control traditional internal combustion engine emissions. In order to reduce vehicle emissions, environmentally-friendly new-energy vehicles, such as electric vehicles and plug-in hybrid vehicles, are being promoted by government policies. The Chinese government plans to boost sales of new-energy cars to account for about five percent of China’s total vehicle sales. It is well known that more electric and electronic components will be integrated into a vehicle platform during vehicle electrification.

A noise source identification technique for the analysis of thermal systems is presented. The proposed method uses transient spectral sound data to assist in determining the source of sound radiation by tracking the variation of the frequency of tones during transient thermal loading (i.e., thermal system warm-up). By considering the temperature dependence of the modulus of elasticity (Young's modulus) it can be shown that structure related tones will decrease in frequency during warm-up. Tones due to propagation of sound in many fluids (i.e., gases and water) will increase in frequency during warm-up due to the temperature dependence of the speed of sound. The analysis method is demonstrated by identifying the source of several noise tones for a pulse combustion furnace.

The growth of auto sales in emerging markets provides a good opportunity for automakers. Cost is a key factor for any automaker to win in an emerging market. This paper analyzes risks and opportunities in a low cost manufacturing environment. The Chinese auto market is used as an example and three categories of risks are analyzed. A typical risk assessment for cost reduction includes the analysis of environment risks, process risks and strategic risks associated with all phases of a product life. In an emerging market, emission regulations are a rapidly-evolving environment variable, since most countries with less regulated emission codes try to catch up with the newly- developed technologies to meet sustainable growth targets. Emission regulations have a huge impact on product design, manufacturing and maintenance in the automotive industry, and hence the related cost reduction must be thoroughly analyzed during risk assessment.

A simple mathematical model was developed and experimentally validated to evaluate how the materials and construction of an automobile tire affect its vibration-radiated noise performance. The mathematical model uses Statistical Energy Analysis (SEA) with modal joint acceptance formulations for wavespeed and radiation efficiency of orthotropically-stiffened and pressurized cylindrical shells. Experimental validation of the model included wavenumber decomposition to determine the dispersion characteristics of an inflated, non-rolling tire in the laboratory. The model is used to conduct a preliminary study into how the various tire constituent materials and construction parameters influence the vibration-radiated noise performance.