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Vehicle manufacturers face increasing challenges in auditing the build quality of their vehicles while considering increasing consumer demands regarding NVH performance. This effect is compounded with the rise in electric and hybrid vehicles. The ability to audit vehicles for a variety of noise types is becoming increasingly important; these include powertrain noise, road noise, and wind noise. An automated measurement system was developed with specific algorithms and sound quality metrics to not only audit vehicle production quality but to add objective data, pass-fail criteria, and trend analysis.

Source-path-contribution (SPC) analysis, or transfer-path-analysis, is a test based method to characterize noise and vibration contributions of a complex system. The methodology allows for the user to gain insight into the structural forces and acoustic source strengths that are exciting a system, along with the effects of the structural and acoustic paths between each source and a receiver position. This information can be utilized to understand which sources and/or paths are dominating the noise and vibration performance of a system, allowing for focused target cascading and streamlined troubleshooting efforts. The SPC process is widely used for automotive applications, but is also applicable for a wide range of product types. For each unique application the basic SPC principles remain constant, however best practices can vary for both measurement and analysis depending on the type of system being evaluated.

Binaural recordings are often used for added realism in subjective listening studies, but are commonly played back in environments that are different than those in which the recordings were taken. An important component of the added realism is the ability of the listener to locate the acoustic sources in a three dimensional space. While humans can generally do a good job of locating acoustic sources through inter-aural time differences (ITD) and inter-aural intensity differences (IID), some well documented ambiguities exist when using these acoustic cues by themselves (i.e. ITD and ILD for a source in front of or behind a listener are identical). To resolve these ambiguities, humans often rely on supplemental information from either direct visual feedback or from their knowledge of and comfort with the listening environment.

The role of NVH test development has changed from addressing a system-level NV concern late in the design cycle (firefighting) to having well established NV optimized test procedures in place. One way this is achieved is by leveraging the information gained during troubleshooting of current product to improve the future product development process for noise and vibration. Today, most NV groups/laboratories use optimized test procedures for creating accurate, consistent, and efficient test results. This still requires expertise to post-process data, compute targets and interpret results to guide product development. This step is often overlooked and, in recent years, due to the lack of NV expertise of “younger” labs (typically in non-automotive industries) or of more established labs affected by the economic downturn (early retirements, lay-offs, especially in the automotive industry) there has been a growing need for automated post-processing “intelligent” procedures.

Design parameters for automotive components can be highly affected by the requirements imposed for vehicle pass-by compliance. The key systems affecting pass-by performance generally include the engine, tires, intake system, and exhaust system. The development of these systems is often reliant on the availability of prototype hardware for physical testing on a pass-by course, which can lead to long and potentially costly development cycles. These development cycles can benefit significantly from the ability to utilize analytical data to guide development of component-level design parameters related to pass-by noise. To achieve this goal, test and analysis methods were developed to estimate the vehicle-level pass-by performance from component level data, both from physical and/or analytical sources. The result allows for the estimation of the overall vehicle-level pass-by noise along with the contributions to the total and dominant frequency content from each of the key noise sources.

As an agricultural tractor OEM was moving a new tractor model from development into production, an objectionable cab “boom” was identified that was not present in the preproduction pilot -level tractors. The cab boom was identified as a low frequency tone causing an increase of 7 (dBA) over the level in the pilot tractors, which was deemed unacceptable. The process used by the tractor OEM engineering team to address this problem has been widely used and refined in the automotive industry, but it is relatively new in the agricultural/off-road vehicle industry. This paper describes the source-path-receiver approach that led to identifying the exhaust tip as the source and the vibro-acoustic coupling of a windshield structural mode with an acoustic cab cavity mode as the path of the boom event.

For the development of a self-propelled crop spraying machine, a hybrid experimental and analytical Source-Path-Contribution (SPC) approach is utilized by a leading agricultural equipment manufacturer. The objective is to predict noise and sound quality in the cab before prototypes are assembled, so that dB(A) and SQ targets can be assessed early on and better specifications sent to suppliers to achieve these vehicle-level targets. The experimental SPC task is conducted on the current crop sprayer model, which has the same cab but different engine, transmission and hydraulics than the new model. A hybrid FE-SEA model of the current cab is developed and run at load cases derived from test data. The SEA approach is needed to evaluate the effect of cab acoustic treatments, which are not accounted for in the SPC experimental model. Contributions to in-cab noise for the current sprayer are estimated from both experimental and analytical SPC.

Identical fiber wheel liners were installed on two different mid size vehicles in order to compare the noise reduction for each vehicle. The fiber liners represented material in current production. A baseline noise level was established with the existing plastic wheel liners and then comparisons were made with fiber wheel liners. Noise levels were compared in the wheel well and in the interior for similar vehicle operating conditions. For both vehicles, significant tire noise reduction at the source was measured with fiber liners compared to plastic liners. One of the vehicles also demonstrated noise reduction in the passenger cabin with fiber liners. Insight into potential explanations for these differences was provided by comparing the noise levels at different locations within the vehicles. The results show how fiber liners are an additional tool to reduce the noise in a vehicle and how the NVH design for the balance of the vehicle can leverage the NVH impact of these parts.

Acoustic source identification is an important issue in both early and prototype validation stages of NVH design. OEMs and suppliers need to assess the entire description of vehicle noise emission, to understand and address interior comfort and exterior radiation issues. Today, none of the existing methods allow engineers to get a quick snapshot of sources contributing to the external pressure level affecting pass-by noise emission compliance, requiring long and arduous testing projects with & without physically masked components. A new acoustic imaging technique provides an important solution. The method is based on a microphone array. Like a camera, but unlike current holographic methods, the software delivers focused, near-realtime 2D colour snapshots and movies, corresponding to the sound pressure level at the region of interest. Typically, the entire side of a vehicle can be analysed during one pass-by run.

The sound field in a vehicle is one of the most complex environments being a mixture of multiple, correlated and uncorrelated sound sources. The simulation of vehicle interior sound has traditionally been produced by combining multiple test results where the influence of one source is enhanced while the other sources are suppressed, such as towing the vehicle on a rough surface for road noise, or measuring noise in a wind tunnel. Such methods are costly and provide inherent inaccuracies due to source contamination and lack of synchronization between sources. In addition they preclude the addition of analytical predictions into the simulation. The authors propose an alternative approach in which the component sounds are decomposed or separated from a single operating measurement and which provide the basis for accurate sound synthesis.

A continuously growing demand comes from the automotive industry for optimization of materials and sound insulating product packaging inside the car, so as to propose the best acoustic performance at reduced costs. A new acoustical holography system provides part of the solution to meet such a demand. The capability of measuring the acoustic field inside a vehicle with high spatial resolution makes it an advanced tool for performing extensive studies of the acoustic transparency of car openings and interior components in various environmental conditions (acoustic chamber, on road, in wind tunnel).

Experiencing the results of virtual NVH analysis in an immersive physical simulation is the only accurate method of developing vehicle, system or component targets and designs. This paper describes an engineering approach specifically created to enable physical interaction with test, CAE and hybrid NVH models, at every stage in the vehicle design process from concept to full detail. It explains the need for sound and vibration decomposition and synthesis, and interactive sound and vibration replay. Implementation of this process has led to the development of engineering tools that enable Interactive NVH Simulation. The paper also describes the practical use an engineer can make of a ‘rapid prototyping’ desktop NVH simulator in the design process. A full scale NVH Simulator is then used to allow evaluation of final design alternatives under realistic driving conditions by non-specialists (i.e. the customer) as well as specialists.

Noise source identification is becoming a key issue in the dimensioning and troubleshooting steps of the design process. In the automotive industry, OEM's and suppliers need to assess the entire description of vehicle noise emission, both for interior comfort and exterior radiation concerns. The resolution of pass-by noise issues pose one of the most significant problems to vehicle designers. While many commercially available systems allow the evaluation of the overall noise emission at any speed and position during the test the task of identifying specific sources is still mainly performed using component masking. A new measurement technique has been developed using a microphone array (typically 2m × 2m with 64 transducers or more) and acoustic beamforming techniques that allows visual source identification at any point during the test. Typically, the entire side of a vehicle can be evaluated with one single measurement run.

In the design of an automobile, an important consideration is to minimize the amount of “boom” noise that the vehicle occupant could experience. Vehicles equipped with four cylinder engines can experience powertrain boom noise in the 40 to 200 Hz frequency range. Boom noise can also be generated by road input, and it is just as annoying. In this paper, a CAE methodology for predicting boom noise is demonstrated for a vehicle in the early design stage in which only 3-D CAD geometry exists. From the CAD geometry, a detailed finite element (FE) model is constructed. This FE model is then coupled with an acoustic model of the interior cavity. The coupled structural-acoustic model is used to predict acoustic response due to powertrain inputs. As a part of the detailed design process, various design modifications were considered and implemented in the vehicle system model. Many of these modifications proved successful at reducing the boom levels in the vehicle.

With the extensive improvements achieved in vehicle driveline and road noise quality manufacturers are turning their attention to component and ancillary noise sources and expecting their suppliers to include sound quality in the assessment of their designs. This paper describes an investigative project into the principal components contributing to the perceived sound quality of powered seat adjusters in passenger vehicles and the statistical methods of analyzing jury preference data.

As worldwide competition for agricultural and construction equipment increases, manufacturers need to distinguish their products in areas such as operator comfort and perceived quality. Advances in digital audio recording and high speed computers have presented the noise and vibration engineer with the possibility of new tools and techniques for analyzing and processing sound. This paper discusses some of the recent developments in sound quality analysis in passenger cars and how they can be applied to similar engineering problems in off-highway vehicles.