Browse Topic: Sound quality
Airplane manufacturers running noise tests on new aircraft now have a much cheaper option than traditional wired microphone arrays. And it’s sensitive enough to help farmers with pest problems. The wireless microphone array that one company recently created with help from NASA can locate crop-threatening insects by listening for sound they make in fields. And now, it’s making fast, affordable testing possible almost anywhere.
Electric vehicles offer cleaner transportation with lower emissions, thus their increased popularity. Although, electric powertrains contribute to quieter vehicles, the shift from internal combustion engines to electric powertrains presents new Noise, Vibration, and Harshness challenges. Unlike traditional engines, electric powertrains produce distinctive tonal noise, notably from motor whistles and gear whine. These tonal components have frequency content, sometimes above 10 kHz. Furthermore, the housing of the powertrain is the interface between the excitation from the driveline via the bearings and the radiated noise (NVH). Acoustic features of the radiated noise can be predicted by utilising the transmitted forces from the bearings. Due to tonal components at higher frequencies and dense modal content, full flexible multibody dynamics simulations are computationally expensive. Based on previously developed metrics for sound quality, a methodology is proposed with the requirements
Design verification and quality control of automotive components require the analysis of the source location of ultra-short sound events, for instance the engaging event of an electromechanical clutch or the clicking noise of the aluminium frame of a passenger car seat under vibration. State-of-the-art acoustic cameras allow for a frame rate of about 100 acoustic images per second. Considering that most of the sound events introduced above can be far less than 10ms, an acoustic image generated at this rate resembles an hard-to-interpret overlay of multiple sources on the structure under test along with reflections from the surrounding test environment. This contribution introduces a novel method for visualizing impulse-like sound emissions from automotive components at 10x the frame rate of traditional acoustic cameras. A time resolution of less than 1ms eventually allows for the true localization of the initial and subsequent sound events as well as a clear separation of direct from
Encapsulations of E-drive systems are gaining importance in electric mobility, since they are a simple measure to improve the noise behavior of the drive. Current experimental evaluation methods, however, pose substantial challenges for the test personnel and are associated with considerable effort in both time and cost. Evaluating the encapsulation on an e-drive test bed, for example, requires a functional e-drive and test bed resources. Evaluations in the vehicle on the other hand make objective assessments difficult and are subject to increasingly limited availability of prototype vehicles fit for NVH testing. To overcome these challenges, AVL has developed a new experimental evaluation method for the NVH efficiency of e-drive encapsulations. In this method, the e-drive is freely suspended in a semi-anechoic chamber and its structure is excited using shakers while the radiated noise with and without encapsulation is measured. The NVH efficiency of the encapsulation is evaluated by
The active sound generation systems (ASGS) for electric vehicles (EVs) play an important role in improving sound perception and transmission in the car, and can meet the needs of different user groups for driving and riding experiences. The active sound synthesis algorithm is the core part of ASGS. This paper uses an efficient variable-range fast linear interpolation method to design a frequency-shifted and pitch-modified sound synthesis algorithm. By obtaining the operating parameters of EVs, such as vehicle speed, motor speed, pedal opening, etc., the original sound signal is interpolated to varying degrees to change the frequency of the sound signal, and then the amplitude of the sound signal is determined according to different driving states. This simulates an effect similar to the sound of a traditional car engine. Then, a dynamic superposition strategy is proposed based on the Hann window function. Through windowing and superposition processing of each sound signal segment
Sound signature design is gaining more importance within global auto manufacturers. ‘Sportiness’ is one of the important point to consider while designing a sound character of a car for passionate drivers and those who love aggressive driving. Nowadays automobile manufacturers are more focused in developing a typical sound signature for their cars as a ‘unique design strategy’ to attract a niche segment of the market and to define their brand image. Exhaust system is one of the major aggregate determining the sound character of ICE vehicles which in turn has the direct influence on the customer perception of the vehicle and the Brand image and also the human comfort both inside and outside the cabin. This research work focuses on novel approaches to identify frequency range and order content by a detailed study of subjective feelings based on psycho-acoustics. Sound samples of various benchmark sporty vehicles have been studied and analyzed based on sound quality parameters. Subjective
In this study, a novel assessment approach of in-vehicle speech intelligibility is presented using psychometric curves. Speech recognition performance scores were modeled at an individual listener level for a set of speech recognition data previously collected under a variety of in-vehicle listening scenarios. The model coupled an objective metric of binaural speech intelligibility (i.e., the acoustic factors) with a psychometric curve indicating the listener’s speech recognition efficiency (i.e., the listener factors). In separate analyses, two objective metrics were used with one designed to capture spatial release from masking and the other designed to capture binaural loudness. The proposed approach is in contrast to the traditional approach of relying on the speech recognition threshold, the speech level at 50% recognition performance averaged across listeners, as the metric for in-vehicle speech intelligibility. Results from the presented analyses suggest the importance of
Electrification brings new benchmarks, tools, and challenges to the ongoing battle with noise, vibration and harshness. The complex science of analyzing and abating noise, vibration, and harshness has entered a “new frontier” as the industry transitions to electrified vehicles, experts in the NVH field tell SAE Media. New design and engineering challenges at the component, system, and full-vehicle levels continue to emerge as EV offerings expand beyond the initial wave of predominantly premium-spec products. Engineers note that benchmarking activity and the introduction of new analysis and testing tools related to NVH mitigation are at “crazy” levels. “Our interest in acoustically improved vehicles always is going to accelerate and the NVH technology must always meet customer expectations,” observed Pranab Saha, whose company Kolana & Saha Engineers in Waterford, Mich., specializes in acoustics, noise and vibration analysis and testing. He noted that some of the latest EV designs show
This paper introduces a wholistic approach for design and development of a turbo-charged four-cylinder engine system using the Quality Function Deployment (QFD) methodology for target setting. Additionally, an exhaustive comparison is conducted between the current product’s NVH performance and that of the target product to design the required countermeasures to reach the desired performance. The proposed process consists of subsequent phases; starting with the voice of customer collection and organizing customer clinic, definition of strategic target to reach, specifying the gap between the current product’s performance, and setting the desired target levels to design and develop the required enablers to close the gap. The final phase is the demonstration of the current product with emulated enablers to the stakeholders.
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).
Speaker performance in Acoustic Vehicle Alerting System (AVAS) plays a crucial role for pedestrian safety. Sound radiation from AVAS speaker has obvious directivity pattern. Considering this feature is critical for accurately simulating the exterior sound field of electrical vehicles. This paper proposes a new process to characterize the sound directivity pattern of AVAS speaker. The first step of the process is to perform an acoustic testing to measure the sound pressure radiated from the speaker at a certain number of microphone locations in a free field environment. Based on the geometry of a virtual speaker, the locations of each microphone and measured sound pressure data, an inverse method, namely the inverse pellicular analysis, is adopted to recover a set of vibration pattern of the virtual speaker surface. The recovered surface vibration pattern can then be incorporated in the full vehicle numerical model as an excitation for simulating the exterior sound field. In this study
This contribution describes a novel method for visualizing leakages in automotive structures using a rotating linear array of a few digital ultrasound microphones in combination with a multi-frequency ultrasound transmitter. The rotating array scans the incident sound field generated by the ultrasound transmitter on a circular area. In a typical measurement setup, the ultrasound transmitter is placed in a cavity (e.g. car interior, trunk or similar) and operates at distinct harmonic frequencies at around 40kHz in an omnidirectional fashion. The rotating linear array is operated on the outside of the cavity and captures the sound field escaping through small leakages. While the reduced hardware complexity allows for the design of a lightweight, handheld sound imaging device, the algorithmic portion of the measurement system requires special attention. In fact, established methods of sound imaging like beamforming and nearfield holography cannot be applied to signals stemming from moving
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.
The current trend toward hybrid and electric automotive powertrains increases the complexity of the vehicle development and integration work for the NVH engineers. For example, considering that the combustion noise is reduced or absent, secondary noise sources like drivetrain, auxiliary systems, road and wind noise become of relevance in terms of vehicle noise comfort. This trend combined with the shortening of vehicle development cycle, the increased number of vehicle variants and an increasingly competitive marketing landscape, force engineers to front-load their design choices to the early stages of the development process using advanced engineering analysis tools. In this context, innovative technologies such as Virtual Prototype Assembly (VPA) and NVH simulator provide the right support to the engineer’s needs when developing the vehicles of the future. The VPA technology enables target assembly noise predictions using the dynamic substructuring methodology starting from
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