Browse Topic: Noise

Items (6,224)
Recent advancements in system-level NVH (Noise, Vibration, and Harshness) development methodologies have improved target cascading and enabled more efficient system-level optimization. Dynamic substructuring facilitates the virtual integration and modification of multiple subsystems and the prediction of changes in overall transfer functions. In practical automotive applications, advanced frequency-based substructuring has been applied to virtually modify system parameters, such as mass and stiffness, at multiple points in a target system, allowing prediction of the resulting effects and optimization of parameter changes without physical intervention. This study extends the methodology by introducing an enhanced substructuring approach capable of addressing not only basic parameter modifications but also large-scale structural changes. The proposed process involves identifying the characteristics of a base system assembly and a target subsystem, decoupling the subsystem from the
Cho, MunhwanBoelens, JelleReichart, Ronde Klerk, DennisAhn, Jiho
As acoustic requirements for NVH trim components become increasingly constrained by mass, cost, and sustainability targets, traditional approaches to inner dash design based on spatially averaged Transmission Loss (TL) metrics are reaching their practical limits. In fully built vehicles, the acoustic performance of the inner dash is governed by its global insulation capability but also by strong spatial heterogeneity and its interaction with spatially distributed noise sources such as the power unit, gearbox, and tyre-road excitation. This paper presents a test-based methodology for the spatial optimisation of inner dash acoustic performance using reciprocal holography. By applying a calibrated sound power source within the vehicle cabin and measuring the reciprocal response in the engine bay and wheel-arch regions, a high-resolution spatial Transmission Loss “hologram” of the inner dash is obtained under in-situ conditions. The resulting spatial data enables the identification of
Harry, EvanEandi, Giacomo
Noise pollution is a major environmental and health challenge, yet its strong spatial and temporal variability makes comprehensive mapping highly complex. Current approaches under the European Noise Directive (END) provide only partial coverage and often lack temporal dynamics. The NoiseSphere project, funded by the Austrian Research Promotion Agency FFG, develops an AI-based methodology for dynamic, large-scale noise prediction and mapping. A machine learning model is trained on heterogeneous data sources, including semantically enriched open Sentinel-2 satellite imagery, OpenStreetMap road data and existing noise maps. The model is refined through integration of noise emission data and validated using targeted in-situ measurements. A case study in an urban environment (Graz, Austria) demonstrates the model’s applicability. By combining remote sensing, traffic dynamics, and machine learning, NoiseSphere enables predictive noise mapping even in regions not covered by current
Girstmair, Josef
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
Schecker, DanielRittenschober, Thomas
The effect of backing polyurethane (PU) foam material properties on the insertion loss of acoustic insulation pads was investigated. First, the material properties affecting the resonant frequency, which mainly determines the insertion loss, were theoretically identified, and practical methods for calculating both the resonant frequency and the insertion loss of the insulation pad were developed. These methods were then applied to evaluate how changes in material properties influence the resonant frequency and insertion loss of the insulation pad. It was found that Young’s modulus, Poisson’s ratio, and thermal characteristic length are the primary material properties that affect these outcomes. The optimal levels of these properties, which are beneficial for interior noise reduction, are derived and presented in this study.
Chae, Ki-SangLee, MoonseokKim, Hyunwoo
The vibro-acoustic performance of a vehicle is a critical factor in customer perception of quality and comfort, yet optimizing for Noise, Vibration, and Harshness (NVH)—specifically road noise—presents a persistent challenge in the modern automotive development cycle. While advanced Finite Element Method (FEM) analysis is essential, the increasing complexity and volume of CAE simulation data often overwhelm manual interpretation, potentially leading to prolonged development times or compromises in final comfort quality. To address these challenges, this paper introduces the application of CDH/ACE (Autonomous Computational Experiments), a framework that integrates conventional CAE simulation workflows with advanced machine learning in an iterative, cyclic process. This creates an exceptionally user-friendly and self-correcting system that autonomously defines, performs, and learns from computational experiments. By leveraging machine learning algorithms to build robust predictive models
Visser, Rene
Simplicity and electrification of the propulsion system are one of the most important trends in vehicle development and integration process. The complexity of NVH (Noise, Vibration and Harshness) design and refinement is the core challenge to this process. Customers’ expectations of an unnoticeable engine during driving make this challenge more critical [1]. Apart from the overall sound pressure level, the sound quality is even more important due to the lack of noise masking effects [2]. Therefore, the development team has reached an internal consensus that NVH attributes are the top priority in engine development. This paper describes the NVH development process of a dedicated hybrid engine for the range extender electric vehicle (REEV) application, beginning with an introduction to REEV system as well as the operating condition data of long-distance road tests. Based on the road test data, the engine technical specification is defined accordingly and broken down into design targets
Wang, HaoZhang, Guiqiang
Vehicle electrification and increasing demands for driving comfort present significant challenges for designing effective noise control treatments (NCTs) in modern vehicles. Lightweight, low-emission designs often compromise acoustic efficiency. A popular and efficient way of compensating for this is through the use of multi-layer ‘trim’ material configurations to noise radiating surfaces to mitigate noise across a wider frequency range. Traditional 3D finite element models, while accurate and even needed to capture the full dynamic behaviour, become computationally prohibitive for complex automotive structures like firewalls, which feature intricate shapes, high curvature, and material compression. This computational burden limits design exploration and timely noise performance predictions. To overcome these limitations, this paper presents an innovative adaptive higher-order finite element method to evaluate the sound transmission loss (STL) of automotive, including the effect of
Van Genechten, BertVansant, KoenPurohit, BimalEffinger, Veronika
The virtual development of Electric Drive Modules (EDMs) for Battery Electric Vehicles (BEVs) requires proven and predictive methodologies. One part of the development investigates the vibro-acoustic assessment for the low- and high-frequency ranges within the targeted operating range. The efficient use of such a methodology requires an understanding of the accuracy and validity of the achievable results, as well as the derivation of suitable improvement measures for goals that have not been achieved. The use of reference data from experimental investigations and a detailed root cause analysis (RCA), to directly link a specific response and behavior to the excitations, modal content, and transfer functions, is an essential and non-trivial part of the methodology development. This paper describes the development of such a methodology using the example of a new EDM virtual model for Noise, Vibration and Harshness (NVH) analysis, including the simulation approach, validation, and
Klarin, BorislavPevec, DenisResch, ThomasEsposito, SaraD'Alessandro, VincenzoSpanu, Giorgio
This work presents a modular engineering methodology (DiPhyBa - Digital Physical Balance) for the virtual validation of Noise, Vibration, and Harshness (NVH) performance in automotive development. The approach addresses the inefficiency of repeated physical testing across vehicle variants by introducing a structured two-phase process—Launcher and Reskin—centered on quantitative performance indicators with formal acceptance thresholds. In the Launcher phase, a digital replica of the base vehicle is built and iteratively correlated with physical test data. Validation is governed by objective indicators of confidence, conformity, and correlation, each evaluated against predefined thresholds. Once validated, the model becomes a certified reference, enabling its reuse across derivative configurations in the Reskin phase. Physical testing is only required if indicators fall below threshold, with a final gate test on pre-series vehicles ensuring industrial robustness. DiPhyBa formalizes the
Celiberti, LuciaCamia, Andrea
The increasing electrification of vehicles means that heating, ventilation and air conditioning systems have a broader range of tasks and a different priority assessment. In electric cars, air conditioning systems are not only responsible for cooling the passenger compartment, but also for controlling the battery temperature, particularly during rapid charging, which represents a high-load operating point. Furthermore, achieving high thermodynamic efficiency is desirable, as this directly impacts the range of electric cars. The elimination of the combustion engine as a major source of noise prioritizes the noise, vibration and harshness behavior of the refrigerant compressor for product selection. To investigate the vibration and acoustic behavior, as well as the fluid dynamic forces resulting from the cyclic compression principle of an electric refrigerant compressor, a test rig was developed that allows compressors to be operated and measured in isolation in an anechoic chamber under
Beer, GabrielSaur, LukasSchwarz, ManuelZemsch, StefanBecker, Stefan
High-frequency whine from electric drive systems has become a critical issue restricting the improvement of vehicle sound quality. Traditional evaluation methods struggle to accurately identify masked whine risks in the early research and development (R&D) phase, due to incomplete hardware of prototype vehicles and high interior background noise. This often leads to problems being delayed until the mass production stage, resulting in high rectification costs. To address this issue, this paper proposes and validates an early risk assessment method based on the Tone-to-Noise Ratio (TNR). First, the generation mechanism of Electric Drive (E-Drive) whine is systematically analyzed, identifying the electromagnetic noise of the electric motor and the gear whine of the reducer as the two dominant noise sources. To address this bottleneck, the TNR psychoacoustic metric is introduced to quantify the perceptual salience of tonal noise relative to background noise, which effectively mitigates the
Yun, ZhaoHui, HuiGao, PanXiao, ZhongdiZan, ChenTeng, Charlie
Achieving best-in-class Noise, Vibration, and Harshness (NVH) in electric powertrains demands a paradigm shift in development methodology. This paper presents a practice-oriented overview of simulation methods in NVH development methodology for electric drive units. This includes target cascading and multi-objective optimisation, and by attacking NVH at the source using KPIs early in the design cycle, significant reductions in development time and reliance on traditional testbed loops are realised. Machine learning (Neural Network) algorithms are utilized to find the best-in-class design, using multi-objective optimisation as well as refining simulation accuracy by adding tolerance effects while target cascading ensures alignment of system-level performance objectives down to subsystem contributions. Combined, these strategies enable rapid and robust NVH optimisation, using simulation for next-generation electric powertrain development. Several applications and real-life examples
Mehrgou, MehdiGarcia de Madinabeitia, InigoGraf, BernhardGojo, Josef
Space vector pulse width modulation (SVPWM) induces common-mode voltage (CMV) in three-phase voltage-source inverters, producing steep voltage edges that can lead to high leakage currents. In electric drive applications, these currents accelerate motor bearing degradation and may cause winding insulation failure. Active-zero-state PWM (AZSPWM) and near-state PWM (NSPWM) have been proposed as alternative modulation strategies to mitigate CMV and reduce drive degradation. This paper investigates the noise, vibration, and harshness performance of AZSPWM and NSPWM in comparison with conventional SVPWM. The proposed CMV reduction schemes are evaluated in terms of both CMV mitigation and their impact on high-frequency sideband vibration harmonics. Experimental results demonstrate that the CMV reduction strategies are highly effective in lowering CMV levels relative to SVPWM; however, this benefit is accompanied by an increase in vibration levels, which may adversely affect the mechanical
Khamis, Mahmoud AlyTatar, Andrei AlexandruRepecho, VictorDoria-Cerezo, Arnau
To minimize noise caused by interior components rubbing against each other, automotive materials are usually tested in advance with the established stick-slip method according to VDA standard 230-206. This procedure is widely used for soft materials, upholstery and plastics. However, it is limited to constant climatic and selected loading conditions. Contrary, in real application, changing climates and dynamic excitations can nevertheless trigger noise issues even in materials rated as suitable in the prior tests. To address this gap, a new test method has been developed that evaluates the stick-slip behavior of material combinations for a wide range of loading and climatic conditions. Conducted in a climate chamber with a standard stick-slip test bench, the procedure applies sinusoidal excitations, dynamic climatic shifts and advanced data analysis. In addition to the usual results the new method also evaluates realistic scenarios such as starting a vehicle in different seasons or
Fritz, SusanneStrangfeld, Martin
Noise phenomena in automobiles caused by the stick-slip effect are increasingly among the most frequent reasons for customer complaints and therefore represent a critical vehicle quality attribute. To proactively address such issues, stick-slip testing of contacting material pairs is commonly applied during development. However, the predictive capability of current stick-slip test methods remains limited, particularly when highly flexible materials and realistic, stochastic excitation conditions are involved. The flexibility of sealing systems often allows the actual relative motion at the contact interface to be accommodated through adhesion and elastic deformation, thereby delaying or even preventing sliding. To date, this effect has not been represented by any characteristic parameter in conventional stick-slip testing. Instead, existing evaluations focus exclusively on the analysis of occurring stick-slip oscillations. For the initiation of stick-slip phenomena, however, not only
Strangfeld, MartinFritz, SusanneWeber, JensRosell, Anneli
The deployment of high-power DC charging infrastructure for electric vehicles introduces new challenges in managing noise, particularly in public environments where acoustic comfort and regulatory compliance are essential. Noise emissions from both charging stations and vehicles during charging are a concern for operators of charging parks regarding customer experience and noise immission regulations. AVL employed a structured three-step approach to develop a non-expert tool for assessing the noise radiation of charging stations and vehicles during the charging phase. In a first step, AVL characterized the noise emissions with sound power measurements. Secondly, the measurement results were transferred to the virtual domain. To achieve this, the vehicles and charging station were characterized in the simulation with multiple monopole sources supported by transfer function measurements. This simulation model was validated against the sound power measurement results. After successful
Gojo, JosefPolanz, MarkusGraf, BernhardLangjahr, PacoMehrgou, Mehdi
Although propulsion noise often constitutes a minority of the overall noise in electric vehicles, it remains an important quality indicator due to its high-frequency tonal character, which is undesirable even at low levels. There are many factors that influence the interior car levels of propulsion noise, i.e. gear whine and electric motor whine. The primary ones to consider are the electric drive units (EDU) internal forces, but also secondary properties such as EDU housing design and encapsulation, vehicle sound pack and mount isolation play important roles. This work focuses on EDU housing design and more particularly on the housing ribs that enables attachment point stiffness and housing strength, but which can also cause problems in terms of noise radiation. Numerical parameter studies on geometrical properties such as length dimensions, thickness and curvature were performed on single ribs of different types. For each design iteration, the key performance indicators radiated
Lennström, DavidMalm, Oskarwurzinger, JakobCederlund, Johan
Vehicle electrification and accelerated development cycles create a need for virtual Noise, Vibration and Harshness (NVH) development tools which are fast, precise and, seamlessly interchangeable between development sites, suppliers and OEMs. Component-based Transfer Path Analysis (C-TPA), standardized in ISO 20270:2019, enables independent component characterization and integration with virtual models to predict sound and vibration in new assemblies, referred to as Virtual Prototype Assemblies (VPA). However, conventional measurements are labor-intensive, typically restricted to a small number of samples, and overlook production variability. This paper introduces a fully automated, ISO 20270-compliant C-TPA system for non-rigid test benches, featuring a pre-instrumented test fixture with multiple vibration shakers and sensors automatically linked to a data acquisition system for immediate processing. Components can be characterized within minutes, with blocked forces directly
Sturm, MichaelWienen, KevinBrandstetter, MarkusSorber, EricCorbeels, PatrickVerrecas, BartGonçalves, Vinícius
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
Amichi, KamelCalloni, Massimiliano
Vehicle sound packages are usually designed to provide a given level of vehicle Noise, Vibration, and Harshness (NVH) comfort, within weight and cost constraints. Optimal comfort results can be obtained by considering the interaction of all the parts as a full physical system. So far, extensive research has already been performed and published on optimizing vehicle sound packages to achieve effective noise reduction at lowest cost and weight. Nowadays, due to the urgency of the transition to carbon neutrality, sound packages must also address the reduction of the full vehicle life cycle carbon emissions. Sound package components should use materials that have a low emission impact during production and that are suitable for recycling at the end of the vehicle’s life. This entails reconsidering the material solutions chosen for the sound package as a whole, rather than for each individual component. This article describes possible differentiations in the design of a sound package
Courtois, TheophaneCardillo, MarcoCriscione, MattiaGerges, YoussefMassocco, Andrea
Tire exterior noise has become increasingly critical in vehicle acoustics due to two key developments: updated pass-by noise regulations, which amplify the relative contribution of tire noise, and the rise of Battery Electric Vehicles (BEVs), which lack traditional powertrain noise. Design trends in BEVs—such as increased vehicle mass from battery packs and the widespread use of large-diameter, wide, low-profile tires—further intensify tire noise due to stiffer constructions and altered contact dynamics. A common method for predicting tire noise is the source-transfer-receiver model, where the tire is represented by a set of monopoles with volume velocity Q derived from near-field measurements. Acoustic propagation is modeled via p/Q transfer functions. Despite its simplifications, this approach is practical for vehicle development, enabling clear separation between source and transfer mechanisms and facilitating targeted noise control strategies. In previous work, we proposed a
Morin, BenjaminDi Marco, FedericoHorak, JanLafont, ThibaultKim, MinkyuKang, Min KyooYoo, Ji Woo
Electric vehicles (EVs) and internal-combustion-engine vehicles (ICEVs) differ fundamentally in their in-cabin acoustics, notably the attenuation or absence of engine-order content. Prior work reports associations between reduced engine sound, speed underestimation, and poorer speed maintenance; however, research on how EVs’ new sound affects speed perception and control is scarce, and most newer studies focus on comfort and subjective pleasantness rather than speed perception. Addressing this gap, the present study uses a two-interval, two-alternative forced-choice (2AFC) paradigm to directly measure just-noticeable differences (JNDs) in speed under ICEV, EV, and silent conditions. Thirty participants performed a 2AFC task in which, on each trial, they viewed two first-person highway clips (reference vs. comparison) and indicated which appeared faster. Results from ANOVA and post-hoc tests indicate that at the 40 km/h reference speed participants showed no clear differences across
Li, ZhenxianParizet, EtienneColangeli, Claudio
Sound source localization is a fundamental capability for environmental awareness in a wide range of applications, including automotive or automated vehicles. Microphone-array-based signal processing techniques are widely used for this task. However, achieving sufficient localization accuracy often requires a large number of microphones and wide array apertures, which can be incompatible with limited installation space and cost constraints. Moreover, standard array-processing methods often rely on free-field transfer functions. In environments with reflections, diffraction, and scattering, particularly under non-line-of-sight conditions, this mismatch can degrade both accuracy and interpretability. This paper presents a methodology for sound source localization in partially known environments that addresses these challenges by combining two ideas. First, the method reduces sensor requirements by exploiting sequential pressure measurements acquired at different spatial locations along a
Pirro, Giovanni BattistaNijman, EugeneDeckers, ElkeDenayer, Hervé
Noise, Vibration, and Harshness (NVH) performance is critical in the automotive development process, yet identifying the true root causes of unwanted dynamic behavior remains a challenge in full vehicle or system-level finite element (FEM) models. This work demonstrates how Frequency Based Substructuring (FBS) provides an efficient framework for understanding NVH phenomena and facilitates new root cause analysis (RCA) types and processes. To begin, we prove the numerical accuracy of the FBS algorithm deployed in the presented investigation by comparing its results with those obtained with superelements and without substructuring. We point out that because the used FBS process starts with a modal representation of the components rather than their frequency response functions (FRF) a different class of RCA type becomes available. Then we introduce new RCA types starting with an analysis named Modal Influence (MI) that reveals the effect of the modes of any component on a certain response
Herbst, Markus
Recent studies indicate that the door system plays a significant role in the interior noise levels of newly developed vehicles. This research investigates the noise transmission paths through the door system and identifies effective strategies for improvement through a combination of door buck testing and simulation. Specifically, in this study, the finite element method (FEM) was employed for door buck simulation, and the model was validated against vibration test results. Subsequently, acoustic analysis tools were utilized to correlate with noise testing, thereby establishing a process to ensure simulation accuracy. The sound insulation performance for the main areas of the door was experimentally evaluated, and a simulation model with good correlation to these test results was developed. By utilizing both experimental and simulation results, the principal transmission paths were identified, and appropriate improvement strategies for these paths were investigated. The validated
Chae, Ki-SangJang, JinungJeong, HojungDo, HyuncheolHan, JinwooYi, JaebokBak, Seong-JaeJeong, ChanHee
Understanding the physiological impact of vehicle electrification on operators remains an important but underexplored issue in commercial vehicle research. This study quantitatively evaluates the physiological fatigue of drivers and onboard crew members during real-world operation of commercial refuse-collection vehicles by comparing a diesel-powered vehicle with a fuel cell electric vehicle (FCEV). Both vehicles were operated on the same routes under comparable real-world operating conditions, including similar time periods and operational tasks, during municipal waste collection service. Heart Rate Variability (HRV) metrics were obtained from R-R interval (RRI) data recorded using a Polar heart rate sensor. The Root Mean Square of Successive Differences (RMSSD), a time-domain index reflecting short-term parasympathetic activity, and Poincaré (Lorenz) plot area (LP area), a nonlinear HRV index reflecting overall autonomic nervous system modulation, were calculated. In-cabin vibration
Utsumi, AtsukoYakoh, Takahiro
Reconstruction of acoustic radiation from vibrating structures is central in vibroacoustics, as full-field sound information is essential for identifying radiation mechanisms and improving structural-acoustic performance. Conventional microphone-based measurements are limited by spatial sampling constraints and high experimental cost, while purely numerical approaches such as Finite Element Method (FEM) simulations offer flexibility but are strongly affected by parameter uncertainties, discretization errors, and imperfect boundary conditions. To overcome these drawbacks, this work develops a hybrid time-domain framework to reconstruct the radiated acoustic field by coupling vibration measurements to a FEM-based vibroacoustic model. The FEM model is reduced using Krylov subspace projection, yielding a compact state-space representation that captures the dominant vibroacoustic modes while remaining computationally efficient for sequential data assimilation. The acoustic radiation domain
Dong, LuyaoCai, YinshanDenayer, HervéDeckers, Elke
It is a general practice to test aero engines to evaluate their performance in specially designed indoor test facilities after assembly, repaired or overhaul. Acoustic features are provided in the test facility to attenuate the noise level to a comfortable and acceptable level. Design of these features specially air intake and exhaust silencers are a challenging task in a flow field like aero-engine test facility considering the very high sound pressure level generated by them during test containing a very wide frequency band. Moreover, growing population and location of these facilities in the vicinity of residential areas has added this challenge in multifold. Also, the capital investment in building these facilities is huge due to their large size and longer construction time. Hence, the correct execution at first shot including design, fabrication and commissioning is very important. An attempt has been made to reduce design errors or improve the accuracy in the design stage by
Gouda, Bansidhar
Global Navigation Satellite System (GNSS) receivers are widely being used in aerospace as well as automotive applications primarily for navigation applications. ISRO uses indigenously developed GNSS receivers in its Launch vehicles (LV) mainly for POD (Preliminary Orbit Determination) and for INS aiding in long duration missions. Advanced GNSS receivers are being developed and used in ISRO’s new generation launch vehicles for closed loop guidance (CLG) applications. Being used in CLG, continuous solution availability and robustness of GNSS solutions are of paramount importance. From April 2023 onwards, GNSS receivers on-board ISRO’s LV missions have shown degraded performance in terms of reduction in no. of satellites tracked and in some cases loss of GNSS solution as well. This was seen in multiple missions and was analyzed in detail. It was observed that there is nearly 3-4dB reduction in carrier to noise density (C/No) ratio and corresponding change in RF AGC gain is also observed
A, Mohammed BasimO T, Anand ShankaraV S, BijuV Gopal, BijuV S, VinojK, BalanC, Radhakrishna Pillai
In order to achieve the research objective of simultaneously improving the air volume and reducing the noise of centrifugal fans, a combination of orthogonal experimental design, BP neural network modelling and multi-objective genetic algorithm (NSGA- II) was used to find the optimal method, and the worm tongue placement angle φ, worm tongue radius R, expansion angle θ and outlet expansion section height L of the worm casing were selected as optimization variables. The air volume and noise of the centrifugal fan under the design working condition were calculated by non-constant and constant calculations, and the air volume and noise were used as the optimization objectives. The results demonstrate that, compared to the initial design, the optimized fan model achieved a noise reduction of 10.99 dB and an airflow increase of 1.76%. Furthermore, the amplitude of the pressure pulsation coefficient at the blade passing frequency was significantly reduced at the monitoring point near the
Huang, GuoxingZhang, WeihongLi, Weichang
Causal discovery within time series is crucial for revealing the actual causal mechanisms in dynamic systems, and it has major impacts in various fields like economics, healthcare, and climate science. Even though it’s important, accurately figuring out causal relationships from observational temporal data is still quite a difficult task. Traditional Granger causality based methods are often limited by noise sensitivity, large amount of data, and the inability to distinguish between real causality and false correlation caused by hidden factors. In order to solve these problems, this paper presents CausalAugVeri, which is a new algorithm that cleverly mixes data augmentation with causal verification to make causal discovery more solid and precise. This work has three main points: First, we carefully check that using convolutional data augmentation techniques can greatly improve how well time series predictions work, giving a steadier base for detecting Granger causality. Second, the
Yang, JingChen, XiaotaoQin, XuanliXu, XianjunHu, Zhangxiang
In a traditional electric vehicle, managing its battery thermal performance is of prime importance. A well-designed battery thermal management system helps in extending its life and avoids safety-related issues like thermal runaways. A critical part of this thermal management is the battery cooling system (BCS), which can be air- or liquid-cooled. Based on the vehicle battery pack size, location, and its design complexity, the original equipment manufacturer can opt for either of the previous two methods. An air-cooled type of BCS system usually involves an active ventilation fan to dissipate the battery heat in the surroundings, which brings symbiotic noise into the picture. In an air-cooled BCS system, the primary source of noise is the cooling airflow over the heat exchanger caused by the fan. The airflow and noise performance characteristics of this fan are typically measured by the supplier in a standalone condition. These performance parameters deviate greatly when the fan is
Nomani, MustafaDupatti, DarshanNikam, KrishnaSasikumar, R.Kajagar, SureshPanchare, DattajiAgalawe, Kiran
Dog clutches have long been employed in the automotive industry across various applications, including transmission systems, transfer cases, axle disconnects, and hybrid driveline architectures. Their ability to provide direct mechanical engagement makes it ideal for torque transmission with minimal energy loss. However, the transition between engaged and disengaged states can introduce noise, vibration, and harshness (NVH), which may be perceptible to vehicle occupants and affect overall driving comfort. A typical dog clutch relies on interlocking teeth for torque transfer, and its actuation can result in NVH due to factors such as friction between mating surfaces, backlash between engagement components, teeth-on-teeth contact during synchronization, and impact forces during clutch engagement. This paper presents Stellantis’s approach to controlling the actuator system to mitigate NVH effects during clutch engagement and disengagement, focusing on strategies that enhance drivability
Xu, ChengyiMadireddy, Krishna ChaitanyaVerhun, Brandon
Passenger comfort is becoming the forefront of luxury private jets where noise needs to be kept to a minimum. One source of structure-borne noise is the vibration of the Passenger Service Unit (PSU) panel. These vibrations originate from the outer skin, excited by turbulent boundary layer, and are transmitted through the fuselage frame to the PSU panel. This panel resides overhead of passenger seating, it is composed of a corrugated honeycomb core sandwiched between thin face-sheets. This paper presents a systematic approach to improve the vibro-acoustic performance of a honeycomb core sandwich structure by employing core filler and facesheet patches. Topology Optimization (TO) is used to determine the optimal layouts of these design modifications. The vibro-acoustic performance of the PSU panel with facesheet patches and core filler is evaluated using a frequency response analysis in the commercial finite element solver OptiStruct. The effectiveness of vibration reduction will be
Russo, ConnorWhetstone, IsobelPatel, AnujWotten, ErikKim, Il Yong
In response to increasing customer demand for enhanced passenger comfort and perceived vehicle quality, OEMs in automotive and commercial vehicles are placing significant emphasis on reducing the interior cabin noise. At highway speeds, wind noise is a primary contributor to the overall noise within the vehicle cabin. Conventional approaches to predict vehicle wind noise rely on physical testing, which can only be conducted in the later stages of the design process once a physical prototype is available. Increased adoption of established computational fluid dynamics (CFD) methods has enabled earlier assessment. However, such simulations require several hours to complete, posing a challenge in the context of rapid design iteration cycles. With the growing adoption of artificial intelligence in engineering, machine learning (ML) approaches have been proposed to predict a vehicle’s aerodynamics performance. Nevertheless, development of ML techniques in the context of aeroacoustics
Higgins, JohnFougere, NicolasSondak, DavidSenthooran, SivapalanMoron, PhilippeJantzen, AndreasBi, JingOancea, Victor
High-fidelity 3D reconstruction of large-scale urban scenes is critical for autonomous driving perception and simulation. Existing neural rendering methods, including NeRF and Gaussian-based variants, often face challenges like unstable geometry, noisy motion segmentation, and poor performance under sparse viewpoints or varying illumination. This paper presents a self-supervised Gaussian-based framework to address these challenges, enabling robust static–dynamic decomposition and real-time scene reconstruction. The proposed method introduces three innovations: (1) a semantic–geometric feature fusion module that combines semantic context and geometric cues for reliable motion prior estimation; (2) a cross-sequence geometric consistency constraint that enforces depth and surface continuity across time and viewpoints; (3) an efficient Gaussian parameter optimization strategy that stabilizes geometry by jointly constraining scale and normal updates. Experiments on the Waymo Open Dataset
Feng, RunleiWang, NingZhang, Zhihao
The Stellantis North America Aero-Acoustic Wind Tunnel (AAWT) has been upgraded with a cutting-edge 5-belt Moving Ground Plane (MGP) system, featuring an 8.5-meter center belt and four Wheel Spinning Unit (WSU) belts with advanced coatings for durability and visibility. The expanded 9.4-meter turntable enables ±90° yaw and supports vehicles with wheelbases from 1800 mm to 4500 mm and weights up to 5000 kg, accommodating the full Stellantis North America product range. The original 2-stage boundary layer control system was retained, with new tertiary slots added for improved flow quality. A high-stiffness, six-component Horiba balance with integrated calibration weights and tractive force measurement ensures accurate and precise measurements. Facility enhancements include a 550 m2 building addition for equipment and vehicle prep, a dedicated compressor container for clean air supply, and a vehicle underbody wash booth for efficient cleaning. Commissioning confirmed that flow quality
Lounsberry, ToddLadouceur, BrentFadler, Gregory
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
Baladhandapani, DhanasekarJadhav, VishalDu, Isaac
In vehicle development, noise reduction is critical for ensuring passenger comfort. As electric vehicles become prevalent and engine noise is minimized, wind noise becomes more noticeable. Modulated wind noise, which causes a sense of fluctuation due to atmospheric turbulence, wind gusts, and preceding vehicle wakes, can cause significant discomfort. This noise is characterized as a high frequency sound above 1 kHz, modulated at low frequencies owing to the wind velocity and direction fluctuating at several Hz. The mechanisms behind wind noise modulation are not fully understood, and no established countermeasures have been developed. This is because wind noise perceived through the side window is primarily caused by the A-pillar vortex and door mirror wake, which coexist as complex turbulent flows around the vehicle. Therefore, identifying the source of modulated wind noise around vehicles under fluctuating wind conditions is difficult. This study aims to identify the source of the
Tajima, AtsushiHirata, TakumiIkeda, JunKamiwaki, TakahiroWakamatsu, JunichiTsubokura, Makoto
Modern aeroacoustic wind tunnels are required to have flat axial static pressure distribution, very low background noise levels, and minimal low-frequency pressure fluctuations. These characteristics enable accurate measurement of aerodynamic forces acting on a vehicle as well as identification of noise sources. The collector of an open-jet or ¾ open-jet wind tunnel plays a critical role in achieving these goals. Collector self-generated noise contributes to the overall background noise level in the test section, and this contribution has become more significant as other noise sources, such as the main fan, have been addressed through improvements to acoustic treatment. Ever-increasing attention to detail is required to manage noise signatures as the overall facility noise floor is lowered. Furthermore, aspects of collector design that may be beneficial to aerodynamics or pressure fluctuation tend to be some of the worst offenders for noise generation. A new collector configuration was
Best, ScottNagle, Paul
LiDAR (Light Detection and Ranging) systems are essential for autonomous driving (AD) and advanced driver-assistance systems (ADAS), providing accurate 3D perception of the surrounding environment. However, their performance significantly deteriorates under adverse weather conditions such as fog, where laser pulses are scattered by airborne particles, resulting in substantial noise and reduced ranging accuracy. This scattering effect makes it difficult to detect objects within or behind particulate matter, posing a serious challenge for reliable perception in real-world driving scenarios. To address this issue, we propose an algorithm that combines adaptive multi-echo signal processing with a feature-integrated, rule-based denoising framework to enhance LiDAR performance in noisy environments. The multi-echo approach selectively utilizes meaningful signal returns by evaluating both intensity and relative echo positions. Based on predefined rules, the algorithm identifies the echo most
Kaito, SeiyaZheng, ShengchaoFujioka, IbukiBeppu, Taro
Inverters are typically integrated into electric drive units for electric vehicles (EVs) to reduce packaging size and cost. However, coupled vibrations from the electric motor and gears are transmitted to the inverter, which can become a dominant noise source due to its large radiative panel. Metal panels are required for electromagnetic interference (EMI) compliance, yet these covers usually lack sufficient stiffness or damping for noise control. Adding ribs and applying damping treatments result in excessive mass, cost, and packaging challenges. A new bubble sheet panel design has been developed to enhance the structural strength and damping performance of the inverter cover while significantly reducing its mass. A thin sheet of aluminum is welded onto the cover in an optimized pattern that enhances stiffness and damping performance while accommodating packaging requirements. The welding pattern can include logos or artistic designs to improve the panel’s appearance. The metal sheets
He, SongBobel, AndrewNaismith, GregoryYi, WenwenPatruni, Pavan Kumar
The Noise, Vibration, and Harshness (NVH) quality of electric vehicles (EVs) is heavily influenced by the performance of the electric drive unit. As a critical step in production, End-of-Line (EOL) testing of drive units is used to assess and control component-level NVH before vehicle assembly. However, the correlation between EOL test results and final vehicle interior noise quality, which directly impacts customer satisfaction, is not always fully understood. This paper presents a methodology for characterizing and predicting vehicle interior noise quality based on data from drive unit EOL vibration testing. Our study investigates the intricate relationship between drive unit assembly variations, component tolerances, and the resulting vibration response. We establish a robust correlation between these drive unit characteristics and both objective vehicle interior noise levels and subjective customer perception. The findings provide a framework for using EOL data to proactively
Arvanitis, AnastasiosJangid, Kuldeep
The final assembly of electric vehicle (EV) drive units includes an essential End-of-Line (EOL) test to ensure both component integrity and Noise, Vibration, and Harshness (NVH) quality. This screening process, which uses dynamometers to measure vibration signals, is critical for identifying defects before a drive unit is installed in a vehicle. A significant source of failure during this test is gear defects, which can arise from manufacturing or handling issues. Traditional EOL testing methods rely on time-domain analysis and the impulsiveness of vibration signatures to detect these defects, a technique with inherent limitations in accuracy. This paper introduces and evaluates a novel approach using Machine Learning (ML) to analyze vibration signals for improved gear defect detection. We discuss the methodologies of both the traditional time-domain and the proposed ML-based techniques. Finally, we provide a comprehensive comparison of their respective efficiency and accuracy
Arvanitis, AnastasiosMichaloliakos, Anargyros
This study presents an image-derived multimodal AI framework for early-stage tire noise evaluation. The proposed model requires only multi-angle photographs captured by a standard smartphone and basic tire specifications. From these images, scaled three-dimensional (3D) meshes and fixed-view depth maps are reconstructed and combined with numerical parameters within a neural network architecture. Three input branches—a point-cloud–gradient branch, a depth-map convolutional neural network (CNN) branch, and a specification multi-layer perceptron (MLP) branch—are jointly trained using a composite loss that integrates frequency-weighted mean squared error (MSE), spectral cosine similarity, FFT-domain consistency, and A-weighted sound-level terms. A dataset of 28 tires, spanning passenger, SUV, and pickup applications for both battery electric vehicles (BEVs) and internal combustion engine (ICE) vehicles, was evaluated using leave-one-out (LOO) cross-validation. The model achieved a mean
Shao, GuangxinShopoff, ScottFranklin, Nicholas
Embedded vision systems are essential for contemporary applications, including robotics, advanced driver assistance systems (ADAS), and intelligent surveillance; yet they frequently experience diminished image quality due to resource constraints, environmental variability, and inconsistent illumination conditions. Such degradations impact multiple visual attributes—sharpness, contrast, color accuracy, noise levels, and structural similarity—that are critical for reliable perception in safety- and performance-driven domains. This study introduces a comprehensive system-level calibration architecture that integrates three coordinated layers: sensor-level adjustment, firmware optimization, and adaptive software enhancements. At the sensor level, exposure control, gain tuning, and white balance adjustments mitigate luminance imbalance and color shifts under changing light conditions. Firmware optimization leverages image signal processor (ISP) parameters to reduce temporal and spatial
Indrakanti, Rama Kiran KumarVishnoi, NitinKamadi, Venkata
The Audio system is an important part of the design of a vehicle cabin. In the vehicle development process, the audio system needs to be tuned for optimal acoustic performance. Traditionally, this process is performed physically on vehicles. In this paper, a methodology is developed to numerically simulate the acoustic performance of the audio system across the full audible frequency range. To provide validation of the method, the p/v acoustic transfer functions (ie., the sound pressure p at the passengers’ ears divided by the voltage inputs v) are measured for different speakers in a production vehicle. As the sound perceived by the passengers depends on both the source and the path, the method development is split into two parts: (a) characterization of parameters that describe the loudspeaker as a source and (b) representation of the vehicle cabin as a path. The speaker parameters are characterized from sound radiation data measured in a 2pi chamber. To represent the vehicle cabin
Yang, WenlongPatra, SureshHawes, DavidShorter, Phil
Pulse Width Modulation (PWM) is needed to supply AC motors from DC voltages, but it creates high-frequency sideband harmonics that contribute negatively to sound quality. Several strategies were developed in the last decades to reduce the total harmonic distortion and switching losses, including discontinuous PWM. A new formulation of discontinuous PWM waveforms is proposed. It eases the implementation of PWM in simulation models and on experimental platforms, but it also enables the creation of new strategies. This study aims at assessing the NVH performance of six new strategies proposed by the authors. The goal is not to enhance the electrical performance but to seek new sound attributes, to change the sound quality of the machine. All strategies were tested on a test bench to characterize their current, vibration, and noise level on the full modulation index range. The measurements performed with the new strategies present some contrast. Semi-discontinuous strategies, which present
Wanty, SaloméDelpoux, RomainGlesser, MartinTotaro, NicolasParizet, EtienneDegrendele, Karine
With the growing trend of electric vehicles (EVs) incorporating regenerative braking systems, many compact SUVs, including hybrids and EVs, still utilize drum brakes on the rear wheels to strike a balance between cost, performance, and durability. Drum brake squeal remains a complex and persistent challenge in the field of vehicle noise, vibration, and harshness (NVH). This issue stems from dynamic instability caused by time–dependent friction forces. Traditional linear modal analysis has been used to study the mechanisms behind drum brake squeal, focusing on harmonic vibrations in large–scale models. However, these methods often fail to accurately correlate with real world behavior due to the presence of extra, non-physical modes. To address this, time–domain analysis approaches have been explored, incorporating detailed friction models and contact mechanics. These methods consider different root causes for high and low–frequency squeal and have shown promising results in accurately
Song, GavinKazimierczyk, StanislausVlademar, MichaelVenugopal, Narayana
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