Search Results

The challenges concerning noise, vibration, and harshness (NVH) performance in the vehicle cabin have been significantly changed by the powertrain shift from a conventional drive unit with an internal-combustion engine (ICE) to electric drive units (eAxles). However, there is few research regarding the impact of electrification on NVH considering the influence of the context such as multi-stimuli and traffic rules during a real-life driving. In this study, the authors conducted test drives using EVs and ICEVs on public roads in Europe and conducted a statistical analysis of the difference in driver impression of NVH performance based on interviews during actual driving. The impression data were categorized into clusters corresponding to related phenomena or features based on driver comments. Furthermore, the vehicles data (vehicle speed, acceleration, GPS information, etc.) were recorded to associate the driver impressions with the vehicle’s conditions when the comments were made.

E-vehicles can generate strong tonal components that may disturb people inside the vehicle. However, such components, deliberately generated, may be necessary to meet audibility standards that ensure the safety of pedestrians outside the vehicle. A tradeoff must be made between pedestrian audibility and internal sound quality, but any iteration that requires additional measurements is costly. One solution to this problem is to modify the recorded signals to find the variant with the best sound quality that complies with regulations. This is only possible if there is a good separation of the tonal components of the signal. In this work, a method is proposed that uses the High-resolution Spectral Analysis (HSA) to extract the tonal components of the signal, which can then be recombined to optimize any sound quality metric, such as the tonality using the Sottek Hearing Model (standardized in ECMA 418-2).

To empirically estimate the radiation of sound sources, a measurement with microphone arrays is required. These are used to solve an inverse problem that provides the radiation characteristics of the source. The resolution of this estimation is a function of the number of microphones used and their position due to spatial aliasing. To improve the radiation resolution for the same number of microphones compared to standard methods (Ridge and Lasso), a method based on normalizing flows is proposed that uses neural networks to learn empirical priors from the radiation data. The method then uses these learned priors to regularize the inverse source identification problem. The effects of different microphone arrays on the accuracy of the method is simulated in order to verify how much additional resolution can be obtained with the additional prior information.

Since NVH is always a property of the whole system, one must have a deep understanding of the dependencies and all the components that interact. The well known in-situ Transfer Path Analysis (TPA) provides methods to separate different components of an acoustical system such as source and receiver. The source including excitation and structural dynamics of the exciting subsystem can be described independently of the structural dynamics of the receiving structure by means of the in-situ blocked forces. The Experimental Modal Analysis (EMA) is a common method as well and aims to identify the structural dynamics of a structure. This paper addresses the combination of both methods using the example of an e-drive of an electric car, which has been analyzed on a test rig. The combination of modal analysis and TPA yields a better understanding of the system and its dependencies.

Quantifying tonalities in technical sounds according to human perception is a task of growing importance. The psychoacoustic tonality method, published in the 15th edition of the ECMA-74 standard, is a new method that is capable of calculating the perceived tonality of a signal. Other methods, such as Prominence Ratio or Tone-to-Noise Ratio do not consider several essential psychoacoustic effects. The psychoacoustic tonality is based on a model of human hearing and thus is able to model human perception better than other methods. The algorithm described in ECMA-74 calculates tonality over time and frequency. In practice, tonalities often originate from rotating components, for example, parts of an electric motor. In these cases, quantification of the tonality of orders is often more interesting than the tonality over frequency. In this paper, an extension of the psychoacoustic tonality according to ECMA-74 is presented.

For many years in vehicle and other product noise assessments, tonality measurement procedures such as the Tone-to-Noise Ratio, Prominence Ratio and DIN 45681 Tonality have been available to quantify the audibility of prominent tones. Especially through the recent past as product sound pressure levels have become lower, disagreements between perceptions and measurements have increased across a wide range of product categories including automotive, Information Technology and residential products. One factor is that tonality perceptions are caused by spectrally-elevated noise bands of various widths and slopes as well as by pure tones, and usually escape measure in extant tools. Near-superpositions of discrete tones and elevated narrow noise bands are increasingly found in low-level technical sounds. Existing pure-tone methodologies tend to misrecognize an elevated noise band as general masking lowering the audibility of a tone in the measured vicinity, whereas perceptually they add.

In the engine development process, the ability to judge NVH comfort as early as possible is a great benefit. The prediction of engine noise on the basis of a prototype engine without the need to install it in a real car significantly speeds up the development process and leads to a cost reduction, as prototype modifications can be evaluated faster. Meaningful predictions of the perceived NVH comfort cannot be achieved just by comparing order levels, but require listening to an auralization of the engine noise at the driver's position. With the methods of Transfer Path Analysis and Synthesis (TPA/TPS) a prototype engine can be virtually installed in a car using test-bench data. The interior noise can be estimated by combining source signals containing near-field airborne noise radiation and mount forces with transfer functions describing the transmission to the target position in the cabin.

In a vehicle's development process, Transfer Path Analysis (TPA) is commonly used for identifying sound sources and their transmission to a receiver. Forces acting on the structure are the reason for the structure-borne sound share of the vehicle interior noise. In practice it is not possible, or too extensive, to measure operational forces directly. Instead, they are often calculated indirectly from accelerations and from additionally measured inertances. As the car body is a strongly coupled system, a force acting at one position results in accelerations throughout the structure. This crosstalk must be considered by using a dense inertance matrix consisting of the ratios between each force excitation and the accelerations at every sensor position. Then a matrix inversion is performed to solve the system of equations describing the coupling of the structure.

The sound sources of modern road vehicle can be classified into three components, driving sound (sound generated through normal driving patterns and events), operating sound (sound generated through actuated components not related to driving), and generated synthetic sound (electronic warning / interactive feedback). The characteristic features of these sounds are dependent upon customer expectation and usage requirements. Additional development complexities are introduced due to each market's cultural and regional differences. These differences in preference must be considered for the establishment of the target sound quality in the early vehicle development process. In this paper, a sound quality goal setting procedure based on user preference is introduced. The sound targets are created as a result of the user preference investigation and validated by intercultural comparison.

With the exact knowledge of the current positions of the microphones in an array and the potential noise sources, it is possible to compensate a relative motion between them. In the past, techniques exploiting this knowledge have been used successfully, e.g., for the measurement of wind turbines and airplane flyover measurement. In this paper, these ideas are applied and modified for the development of a traffic flow observation system. The main purpose of a vehicle pass by measurement is to extract the continuous noise levels of the dominant sources. With the use of advanced video processing or additional sensor information (radar, light barrier) it is possible to create a continuous tracking model of the vehicle. The scan grid in the beam forming algorithm is then recalculated to compensate the movement. In the resulting acoustic video, the vehicle is fixed and the evolution of the sound sources can be observed and auralized for psychoacoustic evaluations.

Since currently a technological shift from automobiles with internal combustion engines now to electric vehicles occurs, new challenges in vehicle acoustics must be met. Although, one of the core duties of NVH engineers will still be the prevention and treatment of disturbing noises, the targeted creation of intended and designed sounds will gain in importance significantly. This sound design task is no longer a choice but a necessity. In the scope of hybrid and electric cars a new kind of acoustic feedback must be created. Surely, the simple electric motor sound, the “tram on wheels”, will not be the final solution accepted by customers. Besides the mandatory use of technical methods like transfer path analysis enabling the reliable identification of the reasons for acoustical problems by separation of sources and transfer paths or binaural panel contribution analysis, investigations of customer preferences on the basis of simulated and real test drives will become more important.

Besides powertrain and aerodynamic noise, tire-road noise is an important aspect of the acoustic comfort inside a vehicle. For the subjective evaluation of different tires or vehicles in a benchmark, authentic sound examples are essential. They should be recorded on a real road rather than on a roller dynamometer (avoiding artificial and periodic sounds, especially in the case of a small roller circumference and a smooth surface). The challenge of on-road measurements is the need for separating the components of the interior noise generated by rolling tires, aerodynamic flow and powertrain. This allows for individual judgment of the noise shares. A common approach for eliminating the engine sound is shutting the engine off after acceleration to the desired maximum speed. Operational Transfer Path Analysis (OTPA) can then be used to auralize the tire-road noise at a certain receiver location, where an artificial head records the interior noise during this coast-down.

The powertrain noise of cars has been reduced in the last decades. Therefore in many cases, rolling tires have increasingly become the dominant sources of vehicles' interior noise. For sound design or a reduction of tire-road noise it is important to know the individual noise shares of the tires and their transfer paths. Authentic tire-road noise can only be measured on a real road, not on a roller dynamometer. So far measurements have been performed during a coast-down on the road with the engine switched off, avoiding the influence of engine noise. Operational Transfer Path Analysis (OTPA) can be used to remove the uncorrelated wind noise, and to synthesize structure-borne and airborne tire-road noise based on input signals measured with microphones at the tires and a triaxial accelerometer at each wheel carrier. Simultaneously, the interior noise is recorded by an artificial head.

Sound quality of vehicles has become very important for car manufacturers. This feature is interpreted as among the most relevant factors regarding perceived product quality. Since the development cycles in the automotive industry are constantly reduced to meet the customers' demands and to react quickly to market needs, ensuring product sound quality is becoming increasingly difficult. Moreover, new drive and fuel concepts, tightened ecological specifications, increase of vehicle classes and increasing diversification, etc., challenge the acoustic engineers trying to create and preserve a pleasant, adequate, harmonious passenger cabin sound. Another aspect concerns the general pressure for reducing emission and fuel consumption, which lead to vehicle weight reductions through material changes also resulting in new noise and vibration conflicts.

Vehicle interior noise consists of a superposition of broadband contributions from powertrain, wind, and tire-road noise. Tire-road noise has become increasingly important referring to overall acoustic comfort, especially for (luxury) sedans with pleasant low-noise engine sounds. An interior noise recording during a coast-down (engine switched off) contains different components: a mixture of wind along with airborne and structure-borne tire-road noise shares. Separating the mixture into these components requires appropriate algorithms and additional measurements. Therefore, structure-borne excitation signals as well as the airborne noise radiation of all four tires are measured simultaneously to an artificial head recording in the vehicle interior during a coast-down test from maximum vehicle speed to standstill.

Predominant brake noise evaluation and rating was developed many years ago and no longer fulfills the need of modern development work. An extended description of a noisy brake event (European expert group guideline EKB 3006) and a standardized test data exchange format, allowing the comparison of different source test results (EKB 3008) are presented. Today's noise rating systems are described and compared by selected examples. The paper proposes an open 4 level noise rating system (EKB 3007). It starts with simple occurrence statistics, noise rating based on sound levels, situational noise rating including duration and finally based on the human perception, described by psychoacoustics.

The development of a new method to evaluate the NVH quality of diesel combustion noise bases upon following questions by regarding typical driving modes: Driving behavior with diesel vehicles Which driving situation causes an annoying diesel combustion noise Judgment of diesel combustion noise as good or bad A suitable test course was determined to regard typical driving situations as well as the European driving behavior. Vehicles of different segments were tested on that course. The recorded driving style and the simultaneously given comments on the diesel combustion noise results to a typical driving mode linked to acoustics sensation of diesel combustion noise. The next step was to simulate this driving mode on the chassis dynamometer for acoustical measurements. The recordings of several vehicles were evaluated in listening test to identify a metric. The base of metric was objective analyses evaluating diesel combustion noise in relevant driving situations.

Clearly, sound quality evaluation has become a central focus for assuring customer satisfaction. To achieve an optimized product sound at an early stage of development, subjective evaluation methods must be combined with analysis and prediction tools to provide reliable information relevant to product quality judgments. Some years ago, a “Hearing Model” was developed explaining and describing many psychoacoustic effects [1], [2], and allowing for roughness calculation in accordance with subjective listening tests [3]. Existing roughness models work well for synthetic signals such as modulated tones or noise signals, but it is challenging to predict roughness for engine sounds because of their more complex spectral and temporal noise patterns [4].

Sound quality of vehicle is more and more an important product feature which significantly influences the perceived product quality. Over recent years, the broad variety of new models, which resulted in increased competition, has lead to rising customer demands with regard to NVH (Noise, Vibration and Harshness) aspects. Apart from the indispensable troubleshooting, the acoustic engineer's scope of work is extended to NVH design engineering. Thus, innovative, ambitious measurement technologies were developed to meet these new, challenging tasks and to maintain a competitive advantage.

Interior vehicle sound is an important factor for customer satisfaction. To achieve an optimized product sound at an early stage of development, subjective evaluation methods as well as analysis and prediction tools must be combined to provide reliable information relevant to product quality and comfort judgments. Binaural Transfer Path Synthesis (BTPS) is a well-known method to calculate interior noise and vibrations based on multi-channel input measurements. Recent enhancements of the BTPS method enable taking into account also simulated excitations, for example engine mount vibrations calculated using MBS and/or FEM simulations, allowing the prediction of interior noise even if the engine is not available in hardware. Interactive evaluation of the generated sounds in a vibro-acoustic driving simulator helps to increase understanding of customer responses and perception of target sounds.