Browse Topic: Sound quality
In vehicles with electrified powertrains, high-frequency tonal noise components have become increasingly prominent and can be perceived as particularly annoying by the driver. While recent advancements in international standardization — such as ECMA-74 [1] and ECMA-418 [2] — have led to powerful new algorithms for tonal noise visualization and analysis, including Tonality-Heatmaps, the measurement side still lacks sensor setups that adequately reflect the spatial sensitivity of noise, especially for tonal components. This challenge is amplified in enclosed vehicle cabins, where room modes create local minima and maxima that become increasingly dense at higher frequencies. As a result, even small head movements can lead to noticeable differences in perceived tonal noise. Current measurement approaches do not sufficiently account for this spatial variability. This contribution addresses the absence of tailored solutions for the driver’s position by introducing an improved microphone arrangement that significantly reduces the uncertainty of measured noise levels. The proposed setup considers spatial variability without compromising comfort or crash safety requirements. By enhancing the precision of tonal noise quantification, this approach provides noise-vibration-harshness (NVH) engineers with a valuable complement to modern software-based tonal analysis methods. The paper discusses the technical implementation constraints and demonstrates the comparability of the new measurement technique with conventional setups.
Electric vehicle subsystems, including powertrains, electric motors, and gearboxes, pose new challenges in achieving stringent acoustic performance targets for both interior and exterior noise. These challenges are intensified by increasingly demanding customer expectations regarding interior acoustic comfort, which encompasses the reduction of intrusive noise sources and the enhancement of overall sound quality across a broad frequency spectrum. A primary concern associated with electric vehicles subsystems is the generation of high-frequency tonal noise, commonly referred to as whine noise, which can significantly impact acoustic performance and passenger comfort. High-frequency whine noise propagates through multiple transmission paths and can be effectively attenuated at the source through encapsulation strategies, which also contribute to broadband noise reduction across a wide frequency spectrum. To predict the acoustic performance of encapsulation, a coupled simulation approach combining the Boundary Element Method (BEM), the Finite Element Method (FEM) and the Poroelastic Finite Element Method (PEM) has been developed. This methodology has been already presented and validated through experimental measurements, demonstrating its acoustic effectiveness in the encapsulation of a generic electric motor housing. While BEM is well-suited for modeling exterior acoustic propagation, standard implementations encounter limitations at high frequencies due to mesh density requirements and computational cost. This work presents hybrid parallelization strategies that integrate frequency-domain decomposition with multi-threading to accelerate BEM H-matrix computations. Frequency decomposition enables parallel processing by distributing independent frequency tasks across multiple processes, while multi-threading enhances performance for fine-grained operations such as matrix assembly and H-matrix compression within each frequency. The processes and improvements enabled by these strategies are discussed and presented within an adapted high-performance computing (HPC) environment.
This paper presents a study of gunshot acoustic signal detectability in the near field of propeller noise, with a focus on the isolation of external gunshot signatures masked by propeller-induced noise. Controlled measurements were conducted in a Recirculation Delayed Anechoic Chamber (RDAC), where acoustic data were collected across varying rotor speeds, source locations, and propagation distances. Propeller noise characteristics were verified using UCD-QuietFly. The recorded signals were analyzed for the acoustic pressure, sound pressure level, and overall sound pressure level directivity to quantify masking effects. Results show that RPM is the dominant factor governing signal detectability. At 3000 RPM, the gunshot signal remains clearly identifiable within the low frequency range of 200–2000 Hz. At 4000 RPM, the signal becomes partially masked, while at 5000 RPM, propeller noise fully dominates and the gunshot signal becomes undetectable. Detectability is further reduced with increasing propagation distance. In-plane microphone locations provide improved detectability. A machine learning-based spectral separation framework was developed to suppress propeller noise and enhance the visibility of impulsive gunshot signatures in multichannel spectrograms. Experimental results show that learning-based denoising is effective at lower RPMs where the signal-to-noise ratio remains favorable, but performance degrades as broadband masking intensifies at higher rotor speeds.
Passenger expectations for quiet and acoustically comfortable vehicle interiors have increased significantly, driven by advancements in electric vehicles and premium audio systems. Acoustic comfort affects perceived quality, communication ease, and overall driving experience. This paper presents a simulation-driven methodology to predict and optimize interior noise performance during the early design phase, focusing on high-frequency acoustic transfer functions and trim material absorption properties. Traditional NVH development relies heavily on physical testing, which is time-consuming and costly. Early-stage predictive tools are essential to evaluate acoustic performance before prototype availability. High-frequency noise (1kHz–12kHz) is particularly challenging due to complex reflections and absorption behavior. Acoustic trims play a critical role in shaping the cabin’s sound field, and their properties must be optimized to achieve desired sound quality. A novel simulation approach is developed using Raytracing (Beam + Particle) to model sound propagation within the vehicle cabin. The method calculates ATFs between point sources (e.g., door panels) and receiver positions (passenger ears), enabling spatially resolved acoustic analysis. This supports early design evaluations by predicting how changes in geometry and materials affect perceived noise levels. Using HEEDS, a DOE-based optimization is performed on frequency-dependent absorption properties of acoustic trims. The trim package includes carpet, headliner, seats, doors, and firewall. The optimization targets mid-to-high frequency ranges where material behavior significantly influences sound quality. Multiple design iterations are evaluated to identify configurations that minimize intrusive noise and enhance tonal balance. A full-vehicle correlation study is conducted to validate the simulation results. Measured ATFs from a physical prototype are compared with simulated data. The acoustic trim package used in the prototype includes all major components. The Raytracing-based ATF model shows strong correlation with measured data. The methodology enables early identification of design choices that degrade or enhance acoustic comfort.
Conventional inverter control uses a fixed switching frequency, which leads to high-pitched switching noise in electric vehicles (EVs) that does not vary with vehicle speed. Although EVs are much quieter than traditional internal combustion engine (ICE) vehicles, some EV owners complain about the lack of dynamic driving sound feedback. A new patented technology has been developed to enhance EV sound quality by dynamically controlling the inverter switching frequencies. This technology generates dynamic propulsion sound with new "switching order" features at multiple harmonics, with the pitch proportional to vehicle speed. A constant pulse ratio between the switching frequency and the electric motor RPM is implemented to control the switching order. This reduces switching losses during low-speed operation and provides boosted acoustic feedback to the driver during acceleration, which enhances driving experience during sports driving. Furthermore, a special "EV shifting" sound that mimics the sound of gear shifting is generated by controlling different pulse ratios at each shifting RPM zone. High switching orders are dropped between neighboring zones to boost lower frequencies for an enhanced dynamic driving experience. These new switching sound features have been validated through electric drive unit and electric vehicle tests. Jury tests confirm the new EV sound with switching orders is authentically generated from electric propulsion system and can be tuned by controlling the switching pulse ratio. This technology has been successfully implemented in the "Watts-to-Freedom" drive mode of the Hummer EV, providing enhanced EV sound feedback, and improving the driver's experience during high-acceleration events.
This paper focuses on the cabin sound quality refinement and the tactile vibration reduction during horn application in the electric vehicle. A loud cracking sound inside the cabin and higher accelerator pedal vibration are perceived while operating the horn. Sound diagnosis is carried out to find out the frequencies causing the cracking noise. Transfer path analysis is conducted to identify the nature of noise and the predominant path through which forces transfer. Based on finding from TPA, various recommendations are evaluated which reduced the noise to a certain extent. Operational Deflection Shape (ODS) is conducted on the horn mounting bracket and on the body to identify the component having higher deflection at the identified frequencies. Recommendations like DPDS improvement on the horn bracket and the body is assessed and the effect of each outcome is discussed. With all the recommendations proposed, the cabin noise levels are reduced by ~ 8 dB (A) and the accelerator pedal vibration levels are reduced by ~ 40%. Sound quality parameter which needs to be considered during the horn selection is explained. The modal criteria which must be taken into account during development phase to avoid the horn cracking noise and tactile vibration is also proposed.
In pursuit of a distinct sporty interior sound character, the present study explores an innovative strategy for designing intake systems in passenger vehicles. While most existing literature primarily emphasizes exhaust system tuning for enhancing vehicle sound quality, the current work shifts the focus toward the intake system’s critical role in shaping the perceived acoustic signature within the vehicle cabin. In this research work, target cascading and settings were derived through a combination of benchmark and structured subjective evaluation study and aligning with literature review. Quantitative targets for intake orifice noise was defined to achieve the desired sporty character inside cabin. Intake orifice targets were engineered based on signature and sound quality parameter required at cabin. Systems were designed by using advanced NVH techniques, Specific identified acoustic orders were enhanced in the intake system to reinforce the required signature in acceleration as well as in cruising mode. A novel decomposition method was developed to identify exact contribution of intake system’s noise from overall in cab noise. Based on advanced NVH analysis and sound diagnosis a precise identification of intake system contributions during both acceleration and cruising conditions was carried out. Furthermore, sound design strategy was developed which targets a dual-mode acoustic profile. The developed design strategy was validated at vehicle level, confirming that the intake system design met both subjective and objective targets. This integrated approach provides a repeatable framework for intake sound design, offering OEMs a robust pathway to differentiate sporty vehicle character through intelligent intake acoustics. This work not only demonstrates the critical role of intake design in vehicle sound signature development but also proposes a systematic methodology for future vehicle sound engineering.
The electric vehicle driveline generates less vibration and noise compared to a conventional internal combustion engine vehicle, making it harder for the driver to perceive the vehicle’s operating status through driveline sounds, thereby diminishing driving engagement and experience. To compensate for the absence of engine sound in EV drivelines, Active Sound Design (ASD) technology has become a crucial method for drivetrain sound enhancement, with sound synthesis algorithms playing a key role in this process. Although pitch-shifting algorithms based on frequency shift principles can synthesize engine sounds, they suffer from spectral leakage and stuttering caused by sound splicing. To address these issues, a pitch-shifting synthesis algorithm (QCPS, Quadratic interpolation-based Continuous audio sample indexing Pitch Shifting algorithm) is proposed in this paper, which combines a quadratic interpolation method with a continuous audio sample indexing strategy. First, the frequency shift coefficient of the sound is calculated. Based on this coefficient, corresponding sound fragments are extracted from the original audio and processed using a pitch-shifting interpolation method to generate the target sound. Then, different interpolation methods are compared for their impact on sound synthesis quality. Meanwhile, a continuous audio sample indexing strategy is developed to ensure seamless sound output. Finally, a simulation program for the QCPS algorithm is developed, and an ASD verification test bench is set up to validate the sound synthesis performance of the proposed QCPS algorithm. The results show that the proposed pitch-shifting synthesis algorithm exhibits minimal spectral leakage and ensures smooth sound splicing. This paper provides an effective solution for compensating EV powertrain sound and enhancing the driving experience.
Acoustic flight testing of rotorcraft often involves generating noise source hemispheres to gain an understanding about the aircraft's acoustic emissions. However, aerodynamically complex Urban Air Mobility and Future Vertical Lift vehicles may not maintain a steady aerodynamic state during flight, making source hemispheres measured using traditional linear arrays unreliable or difficult to interpret. To address this challenge, all emission angles need to be measured simultaneously. This has lead to the concept of the two dimensional 'snapshot' array layout. A mathematically defined microphone distribution was utilized to achieve uniform coverage on the source hemisphere. Within the chosen distribution, two lower microphone count distributions are embedded, allowing for a comparison of the effects of number of microphones. The array was deployed as part of a joint Army/NASA acoustic research flight test in July of 2024. Data were collected using an MD530F helicopter as the test vehicle, executing both steady and unsteady flight. Analysis of the array resolution is used to determine adequate channel count and spatially varying sensitivity to array density.
The author’s life work in acoustics and sound quality, continuous over more than 40 years, has followed a number of branches all involving measurement technologies and their evolution. The illustrated discussion begins 60 years ago in 1965 at Arizona State University in its Frank Lloyd Wright-designed Gammage Auditorium, and moves to the Research and Development Division of Kimball International, Inc. (Jasper, Indiana) in 1976 with piano research using a Federal Scientific Ubiquitous analog real-time FFT analyzer and Chladni-plate-mode studies with fine sand and high-speed photography of sound board modes. It continues at Jaffe Acoustics, Inc., a concert-hall-specializing consultancy in Norwalk, CT, with early-reflection plotting using a parabolic microphone on an altazimuth angular-readout mounting and either photographing oscillograms, or running a high-speed paper chart printer, assembling “wheel plots” incremented every 10 degrees in azimuth and altitude to map reflection patterns. Involvement with binaural technique began for me in 1986 and led me into the automotive industry, whose SQ evolution and that of HEAD acoustics will be outlined along with an earlier side-branch courtesy of James Shedlowsky (GM retired): a photo-archive of GM pseudo-binaural and binaural techniques and jury evaluations starting in 1952 which has been presented in an earlier Noise and Vibration Conference’s Science Fair.
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 reflected sound. The measurement instrumentation uses a rotating linear array of a few digital microphones which granularly scans the incident sound field on a circular area. The proposed method for computing an acoustic image is based on compensating the moving microphone signals for Doppler distortions and evaluating the coherence of the resulting signals with a non-moving reference microphone for each point in the acoustic image. The methodology is evaluated in the context of localizing the periodic engage event of an electromechanical clutch and the clicking noise of the aluminium frame of a passenger car seat under periodic excitation.
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.
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 analyzing the respective transfer functions using simple computational methods. This approach is particularly suitable for conducting initial development iterations or for benchmarking.
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 reflected sound. The measurement instrumentation uses a rotating linear array of a few digital microphones which granularly scans the incident sound field on a circular area. The proposed method for computing an acoustic image is based on compensating the moving microphone signals for Doppler distortions and evaluating the coherence of the resulting signals with a non-moving reference microphone for each point in the acoustic image. The methodology is evaluated in the context of localizing the periodic engage event of an electromechanical clutch and the clicking noise of the aluminium frame of a passenger car seat under periodic excitation.
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 to design a reduced order model, coupling analytical solutions for the electrical motor along with lumped parameter powertrain modelling. Namely, for an adequate representation of the tonal content, the proposed model considers the harmonic excitations of the electric motor and torque ripple, time-varying stiffness and backlash for the meshing gears and flexibility of the housing at the bearing connection points. The reduced order model predicts the transmitted bearing forces, enabling an overview of the sound quality of the radiated noise with lower computational time and complexity.
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 generated by the algorithm, the coherence and real-time performance of the synthesized engine sound are improved, so that the ASGS can quickly and accurately reflect the driving status of EVs. Finally, through the analysis and verification of the sound quality of the synthesized sound through different parameter adjustments, an engine synthesized sound that satisfies the subjective evaluation of sound quality can be obtained. This paper proposes an effective active sound synthesis algorithm for EVs, which ensures that EVs produce more textured engine sound while emphasizing the timeliness of synthesized sound. It plays an important role in improving pedestrian safety perception and driving experience, and promotes the research and development of ASGS for EVs.
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