Browse Topic: Noise, Vibration, and Harshness (NVH)

Items (10,048)
Vehicle vibrations during precision instrument transport can cause damage and failure. Existing vibration isolators often lack reliability, mass production feasibility, and easy maintenance. In this paper, we design and analyze a quasi-zero-stiffness vehicle-mounted isolator with an inerter, decreasing dynamic stiffness while raising the effective mass. Theoretical, simulation, and experimental results show improved isolation performance, lower isolation frequency, and a broader isolation bandwidth.
Li, KaiLv, SiboSun, NingDai, Shijie
With the rapid development of China’s civil aviation industry, the problem of airport noise has attracted widespread social attention. The requirement for the real-time monitoring and evaluation of acoustic environment around airports is becoming more and more intense. The identification of aircraft noise events in the complex acoustic environment surrounding the airport is the most critical technical problem in airport noise monitoring. However, the traditional noise source identification technology is difficult to be widely used in real-time monitoring system due to its large errors and complex deployment conditions. This paper presented an aircraft noise source identification technique based on a single acoustic vector sensor. The azimuth parameters of the noise source were estimated by the three-dimensional spatial positioning algorithm of sound pressure and particle vibration velocity combined with information processing, and the three-dimensional footprint of the noise event in
Hou, JiayuHe, TianlunZhu, LinChen, YingLiu, YinhuiLv, LeiWang, YuhaoChen, Da
In response to the problem of manual transmission rattle noise in the acceleration process of a truck, the mechanism of the problem is analysed, and the scheme is developed and verified from two aspects: reducing the torsional vibration of the system and reducing the response of the transmission gear. The results show that, on the one hand, reducing the clutch stiffness and optimizing the torsional vibration of the system can reduce the rattle noise of the transmission; On the other hand, it can also reduce the rattle noise of transmission gears by improving the engagement precision of transmission gears and reducing the gear clearance. Considering the improvement effect, cost, and influence on other performance of the two schemes, the appropriate engineering scheme is selected to effectively solve the problem and improve the riding comfort of the product.
Yang, ZhijieXu, Binghua
Nowadays, the majority of intelligent fault diagnosis approaches are still centered on individual faulty components, while only a limited number of models are capable of performing integrated diagnosis for rotating systems that consist of shafts, bearings, and gears. Under variable-speed operating conditions, the large scale of vibration data further complicates the process of effective feature extraction. To improve these challenges, this study develops a comprehensive diagnostic framework for rotating components, termed WGAN-SAFC. The proposed architecture integrates a Wasserstein Generative Adversarial Network (WGAN) with a hybrid structure of stacked autoencoders and sparse filtering (SAFC). SAFC integrates the feature-learning capability of SAE and the sparsity-driven representation of SF, while incorporating adversarial data generation to address sample imbalance and enhance fault diagnosis performance. Experimental verification on collected vibration datasets demonstrates that
Li, ShunmingFeng, Mengqi
This SAE Standard establishes the test procedure, environment, and instrumentation for determining the sound levels of snowmobiles in the stationary test mode. This test method is intended to provide an accurate measurement of exhaust and other engine noise and may be used to evaluate new and in-use snowmobiles to determine compliance with noise control regulations. Sound level measurements obtained with this test method are not intended as an engineering determination of overall machine noise. For this purpose, the use of SAE J192 is recommended.
Snowmobile Technical Committee
This article investigates high-frequency noise in permanent magnet synchronous motors (PMSMs) for electric vehicles, originating from pulse width modulation (PWM). A theoretical model is developed to formulate the phase voltage under space vector PWM (SVPWM), explicitly accounting for the additional harmonic components generated by the discrete-time voltage update in digital control systems. This derived voltage waveform serves as the excitation source in an electromagnetic finite-element model, from which the PWM current harmonics and their resulting high-frequency electromagnetic forces are computed. Critical components of the electromagnetic force are then extracted through two-dimensional Fourier transform. A structural model of the motor, incorporating practical assembly constraints, is established and validated by experimental modal tests on a fully assembled motor unit. To enable rapid noise prediction over the wide speed range, vibro-acoustic transfer functions are introduced
Lin, FuChen, Yihui
This paper presents the optimization of a Halbach magnet array applied to an axial flux machine (AFM) in a 12-pole, 18-slots yokeless and segmented armature (YASA) topology, evaluated in the torque–speed characteristics diagram. AFMs offer significant advantages in terms of compact design and high torque density compared to other permanent magnet machine topologies. However, noise, vibration, and harshness (NVH) performance is strongly influenced by cogging torque, electromagnetic torque ripple, and tooth forces. While Halbach magnet arrays are well established in high-performance radial flux machines, only limited research has investigated their influence in AFMs. A Halbach array concentrates magnetic flux on one side of the magnet arrangement, leading to increased air gap flux density and a strongly reduced need of a back iron yoke under the magnets. By using a Halbach array, the magnetic field distribution in the air gap becomes more sinusoidal, thereby reducing harmonic components
Müller, KarstenSchulz, FabianBremer, MartinBurkhardt, YvesDe Gersem, Herbert
This SAE Aerospace Information Report (AIR) outlines a recommended procedure for evaluation of the vibration environment to which the gas turbine engine powerplant is subjected in the helicopter installation. This analysis of engine vibration is normally demonstrated on a one-time basis upon initial certification, or after a major modification, of an engine/helicopter configuration. This AIR deals with linear vibration as measured on the basic case structure of the engine and not, for example, torsional vibration in drive shafting or vibration of a component within the engine such as a compressor or turbine airfoil. In summary, this AIR discusses the engine manufacturer’s "Installation Test Code" aspects of engine vibration and proposes an appropriate measurement method.
S-12 Powered Lift Propulsion Committee
The transition from internal combustion to electric vehicles requires assessing new challenges posed by novel components, materials, and manufacturing processes. These include assessing new types of excitations and damages from a reliability perspective. This paper investigates a solution to enhance Printed Circuit Board (PCB) reliability within automotive Power Electronic Units (PEUs). Controlling vibration levels is crucial to prevent component breakage and PEU failure. The proposed approach exploits Locally Resonant Metamaterials (LRMs) to reduce PCB vibrational loads. LRMs provide excellent Noise, Vibration, and Harshness (NVH) performance within specific frequency ranges while being lightweight and providing high design freedom. Since direct integration into the PCB is unfeasible, the aluminum spider frame securing the PCB is treated instead. Previous simulations demonstrated significant vibrational load reduction. In this study, the LRM solution is fabricated, and experimental
Tincani, SaraClaeys, ClausDeckers, ElkePandiya, NimishDindorf, Christian
For sustainability reasons, the automotive market is requesting 100% monomaterial noise treatments, particularly for the end-of-life recycling without any part separation operation. But also, OEMs require super light, highly performance insulating noise treatments for electric vehicles in order to extend vehicle autonomy. PP melt-blown fiber felts present good mono-material characteristics with very good absorption, but generally not so good insulation properties behind an airtight barrier due to lack of stiffness. Moreover, these PP melt-blown fiber felts are relatively expensive and not thermoformable, thus forcing them to be used as 2D die-cut parts behind existing hard or soft trims classically. The shown optimization approach proposes to return to 100% thermoformable recycled and recyclable PET formulations blending unusual coarse mechanical specific fibers, in order to optimize the viscothermal exchanges, while maintaining good mechanical properties, with microfibers for best
Duval, ArnaudLei, LeiWilkinson, AlexandreDelinselle, Eric
Gyroscopic effects split circumferential traveling-wave resonances of rotating structures into forward and backward branches. This work first analyzes the splitting in the co-rotating (Lagrangian) frame to provide physical intuition for the evolution of the two branches with spin speed. A transformation to the inertial (Eulerian) frame is then derived, showing that the observed frequencies are shifted by a kinematic Doppler-like term that acts with opposite sign on the forward and backward waves, leading to different Campbell-diagram slopes depending on the observation frame. The resulting framework is validated experimentally on a freely rotating, unloaded tire using two complementary sensing modalities: wireless on-tire accelerometers (co-rotating view) and a scanning laser Doppler vibrometer (inertial view). A frequency-domain SVD-based identification (FDD/ODS-SVD) is used to extract poles and deformation patterns over a range of spin speeds, enabling Campbell diagrams in both
del Fresno Zarza, JavierNaets, Frank
Electric high voltage (HV) cables are commonly used in automotive applications and very prominently in electrified vehicles. These cables are potential flanking transmission paths for structure-borne sound in a broad frequency range and must therefore be included in the NVH design process. Electrical high voltage cables exhibit non-linear mechanical characteristics, when exposed to significant bending the internal geometry of the cable will change and a curvature dependent bending stiffness will result. The electrical cables envisaged in the current publication feature a helically wound stranded aluminium wire core. This conductive core is covered by, in sequence, a silicone rubber insulation, a braided aluminium wire shield with aluminium foil to minimize electromagnetic interference and a silicone rubber outer sheath. An extensive measurement campaign was carried out to dynamically characterize cable specimen of different lengths and cross sections in terms of multi-degree of freedom
Nijman, EugeneBuchegger, BlasiusBöhler, ElmarZeller, BernhardRejlek, JanFaksa, LukášLukavsky, David
In recent years, the automotive industry has actively explored the application of various AI-based models such as Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, Autoencoders, and Transformers to improve defect detection rates at the End-of-Line (EOL) stage. However, implementing these approaches in the Noise, Vibration, and Harshness (NVH) area face several practical challenges: ① extended evaluation times compared to other data types, which limit the quantity of training data and lead to overfitting; ② label imbalance caused by the relatively small amount of defect data; ③ reduced labeling accuracy due to human error; ④ decreased robustness under domain shifts such as changes in jig fixtures, test environments, and signal-to-noise ratio (SNR); ⑤ diminished model reliability when new defect arise during development; and ⑥ constraints imposed by compatibility requirements with existing test equipment. This study proposes a Convolutional Autoencoder (CAE
Park, Jun-SeoJo, Hyeon-ChoelCho, In-JeSeo, Jae-YongYoo, Seong-Sik
This paper presents an analytical model for three-phase Permanent Magnet Synchronous Motors (PMSMs) based on Magnetic Equivalent Circuits (MECs). The approach combines a reduced magnetic network, formulated in the complex domain to simplify the mathematical development, with an offline parameter estimation procedure systematically applied for different harmonic orders. This enables the model to capture the spatial dependence of permeance variations and reproduce inductance and magnetic flux nonlinearities, while maintaining generality, physical interpretability, and computational efficiency. Numerical simulations are compared with Finite Element (FE) results to validate the model’s ability to predict current and torque harmonics and the resulting radial electromagnetic forces, demonstrating its suitability for fast Noise, Vibration, and Harshness (NVH) analysis and vibroacoustic optimization.
Luciano, LudovicaDoria-Cerezo, ArnauSalamone, Nicolò
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
When developing a vehicle, the overall body stiffness is an important parameter to be estimated for several automotive attributes. As a complement to the traditional experimental and computational static torsional stiffness assessment, an improved method has been developed to evaluate the body stiffness when driving the vehicle on a test track. This method, valid for both test and simulation, is called Opening Distortion Fingerprint (ODF) and uses the so-called Multi Stethoscope (MSS) to measure the dynamic distortion in each body closure opening and cross section. For evaluating the distortion, from both test and Multi Body Dynamics (MBD) simulation data, the Evaluation-line (E-line) method is used. The E-line method is a linear approach. Consequently, it is only valid in the absence of large rigid body rotations of the vehicle body. Therefore, to assess the validity of the ODF method, it is crucial to identify the frequency at which the distortion results become invalid due to rigid
Olger, EmmaLindkvist, LisaPiiroinen, PetriKarypidis, JohnPena, MiltonBäcklund, JesperAppelgren, PeterMarberg, HenrikUgale, PravinWeber, Jens
The rapid electrification of the automotive industry introduces new challenges in noise, vibration, and harshness (NVH). In particular, in a virtual prototyping phase of the e-vehicles development, the rubber mounts are often one of the key elements to be considered when analysing the structure borne noise contributions. Having an accurate experimental characterization of the mount dynamic stiffness curves is therefore very relevant. However, conventional mount characterization methods are often pushed to their limits, partly due to the use of stiffer bushings, and partly because the frequency range of interest is extended toward higher frequencies. When using inverse substructuring, the dynamic stiffness curves can be obtained from frequency response function measurements. The required test setup consists of excitations and responses, located on each side of the mount via dedicated fixtures. The measured frequency response functions are reduced into 6 degrees of freedom representation
Bianciardi, FabioForrier, BartMinervini, DomenicoBarbieri, MarcoJanssens, Karl
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
Realistic seat vibration reproduction is essential for delivering authentic haptic cues and enhancing driver immersion in driving simulators. Unlike direct playback of road recordings, simulator applications require vibration synthesis that responds interactively to driver inputs and vehicle dynamics. Reproducing these vibrations at the seat is often complicated by actuator bandwidth limitations and the dynamic behaviour of the seat structure itself, which can alter the intended target response. This work presents vibration synthesis and seat dynamics compensation strategies implemented on a single-axis seat vibration reproduction system equipped with a vertical actuator. Frequency Response Functions (FRFs) were measured to characterise the system dynamics under single-axis excitation. Run-up and coast-down tests were conducted on the seat and compared to target responses measured on an actual vehicle under operational conditions. Several seat dynamics compensation strategies were
Muthu Chaiphas, Joshua DanielCuenca, JacquesBianciardi, FabioColangeli, ClaudioDeckers, ElkeDenayer, HervéJanssens, Karl
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
Monitoring inputs and states of a structural dynamic system is often challenging, as direct measurements are costly or even infeasible. A virtual sensing methodology is presented for jointly estimating the input and state of a structure when subjected to multi-directional base excitations. The approach uses a tuned Kalman Filter combined with a model-order reduction of the system model to ensure a low computational cost whilst allowing accurate estimation from a limited number of acceleration measurements. This enables real-time virtual health monitoring strategies and reduction in instrumentation during data acquisition without additional information such as location and direction of application about the inputs. The proposed methodology is validated numerically and experimentally using a notched aluminum beam excited on a multi-directional shaker table, driven simultaneously in two in-plane directions. The study demonstrates accurate full-field estimation of multiple responses along
Salazar Colunga, RodrigoPandiya, NimishDindorf, ChristianNaets, Frank
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
Part- or component-level tests are commonly performed by Tiers and OEMs to investigate the NVH behavior and loading mechanisms. However, because test bench dynamics differ from those of the actual vehicle environment, correlating measured sound, acceleration and forces between bench and vehicle often proves challenging. Blocked forces offer a way to address this issue, as they provide test bench and vehicle independent load representations. This effectively enables different Tiers to deliver consistent load data, which OEMs can then use to better tune excitation and noise transmission on their vehicles. This paper focuses on 2 test bench compensation techniques, involving pure test and a simulation models of the tire to obtain accurate blocked-forces. The compensation techniques are validated on four testbenches of different companies.
Reichart, Ronde Klerk, Dennis
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
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
This study presents a high-fidelity NVH (Noise, Vibration, Harshness) analysis model development process for EV traction motors. The proposed process consists of two main components: Path advancement through structural stiffness tuning, and Source advancement, focused on the motor’s excitation mechanisms. Model accuracy was validated through comparison of simulation results with dyno experiment data, with particular focus on the 24th-order electromagnetic vibration observed in an 8-pole, 48-slot motor. Path advancement was achieved through modal correlation between experimental results and finite element (FE) analysis. Nine modal experiment and simulation stages were conducted, ranging from individual components to the complete motor assembly. Mode shapes were compared using the Modal Assurance Criterion (MAC), and natural frequencies were matched within a 5% error margin by adjusting FE material properties. For the 24th-order electromagnetic vibration, simulation results agreed with
Kim, DongheeKim, Dong-JunLee, SangHanKim, Seon HyeongHwang, Seung GyuValente, GiorgioParisouz, ShahriarHalse, Christopher
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 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
In this study, we propose a methodology for predicting the acoustic modes and natural frequencies of a sedan using artificial intelligence and demonstrate the feasibility of controlling its acoustic characteristics by modifying the hole distribution of the package tray. In typical sedan structures, the cabin cavity and trunk cavity are acoustically coupled through holes in the package tray. The distribution of these holes significantly affects the natural acoustic modes and frequencies of the vehicle. However, once the exterior shape of the vehicle is finalized during the design stage, options for structural modifications to mitigate noise issues caused by these modes become extremely limited. To address this challenge efficiently, we develop a deep learning-based neural network model trained on data derived from a simplified acoustic analysis model of a sedan that includes a package tray. Finite element analysis is performed to generate acoustic modes and natural frequencies, which
Lee, Jin WooCho, JaehoNam, YounsicHan, Yongha
Because of automotive electrification, fan system noises previously hidden by the internal combustion engine could become key contributors to the overall noise behavior. Metrics like overall sound pressure level or Loudness are first order metrics enabling noise ranking. Yet, second order factors, that are relevant to assess annoyance, are not correctly described using a single criterion. This paper studies the applicability of various psychoacoustic annoyance models in an attempt to address the subjective perception of sound quality. Based on pairwise comparisons through a jury test with a set of 8 noises at similar overall levels, the combined impact of several psychoacoustics metrics was previously determined. This computation includes a signal modulation metric, a frequency content balance and a tonal criterion. To complete this approach, the correlation for fan system noise annoyance ranking based on this jury test is compared with several psychoacoustic annoyance criteria. These
Scouarnec, DenisBennouna, Saad
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
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
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
An application of a Non-Parametric Variability Modeling (NPVM), as introduced by Pr. Soize, of a full vehicle road noise simulation, is an opportunity to highlight some applicative issues of such a stochastic approach. First, the convergence of the stochastic computations is considered by introducing the probabilistic modal density of the considered model as an indicator of the system intrinsic dynamic behavior. Since the probabilistic model induces a spread of modal frequencies, the upper range shows a lack of modes, deviating from the actual system modal density. The study of this deviation leads to the modal truncation criterion required to achieve a relevant probabilistic modal density in a targeted frequency range. The required margin in order to achieve a proper convergence of the probabilistic problems appears larger than expected. Then, using appropriate parameters, road noise simulation is investigated in the framework of the stochastic modeling. After the capability of the
Gagliardini, LaurentGlandier, ChristianBauer, EricStraka, AndreasFiedler, Uwe
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
Interior acoustics represent an essential component of driving comfort in electric vehicles. Numerical simulation is an effective approach for assessing design concepts and enhancing acoustic performance. However, a fully coupled vibro-acoustic model for an entire vehicle remains computationally infeasible. Our approach couples mechanical and acoustic modal models on non-conforming interfaces in the low-frequency range, allowing independent mode combinations. Modal coupling reduces the computational effort significantly from full-order systems with millions of degrees of freedom to a selection of modes of the acoustic and mechanical systems. Modal models of the vehicle structure are derived from measurements with a laser-vibrometer and accelerometers while the interior acoustics are simulated numerically. Since laser-vibrometer measurements are restricted to the vehicle’s exterior surfaces and vibro-acoustic coupling occurs between the inner structural surface and the interior fluid
Gutbrod, ManuelGabriel, ChristophMüller, Gregor JohannesToth, Florian
This study investigates the NVH characteristics of the spline coupling that connects the motor and reducer shafts in an electric drive unit, using flexible multibody dynamics simulations. Focusing on the source stage of the NVH analysis process, the excitation force magnitude and spline trajectory are examined under various spline design conditions. The study compares spline fit types (side fit vs. major fit), clearance vs. interference conditions, and variations in tooth number and module size. This study analyzes the overall behavior of spline excitation forces under various design conditions, complementing prior research focused mainly on specific causes or manufacturing improvements. Side fit splines exhibit lower first-order excitation forces compared to major fit splines, but significantly higher excitation forces at higher orders. This leads to increased spline trajectory amplitude and amplified whirling of the input shaft. Since the input gear is directly coupled to the input
Kim, Dong-JunHwang, Seung GyuKim, DongheeKim, Seon HyeongLee, SangHanGrant, GeorgeHalse, Christopher
For analysing flow and acoustic induced structural vibration, a fully run time coupled framework combining a hybrid CFD-CAA approach with a modal response simulation was validated and presented at the ISVNH 2022 (SAE Technical Paper 2022-01-0938). In this paper i We apply this CFD–CAA–modal coupling method to a series-representative bonnet geometry and demonstrate its capability to capture flow and aeroacoustically driven vibration with two-way coupling. ii We analyse the modal properties of the bonnet and show that confined air volumes beneath the bonnet can introduce significant fluid loading effects, which are already embedded in experimentally validated FE modal models and must therefore be treated carefully in two-way coupled simulations. iii We validate the fully coupled aeroelastic simulation against wind-tunnel measurements with undisturbed inflow, show close agreement with the measured vibration response and analyse that the dominant excitation is in this case from below the
Schwertfirm, FlorianOcker, JoergHartmann, Michael
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
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