Browse Topic: Noise, Vibration, and Harshness (NVH)
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
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
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
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
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
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
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
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
The simulation of structure-borne energy flow within a full vehicle trimmed body at mid and high frequencies has always been a challenge due to the large computational cost associated with standard deterministic simulations. This is a particularly pressing problem given that the electrification of the vehicles is extending the presence of structure-borne sources to higher frequencies. While the improvement of computational hardware has allowed OEMs to shift the limit of standard Finite Element (FE) approaches to higher frequencies, no methods have been proposed in the literature that tackle the full frequency range for industrial-sized problems. In this paper, a simulation methodology that uses wave-based processing of the original low-frequency finite element input deck to compute the coupling loss factors is proposed to model structure-borne noise in complex systems at mid and high frequencies. The methodology is validated against numerical and experimental data.
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
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
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
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
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
In the automotive industry, controlling noise transmission through vehicle components is essential for passenger comfort and regulatory compliance. Traditionally, Transmission Loss (TL) is estimated using simplified CAD-based metrics, which lack accuracy at high frequencies and for complex assemblies. Modeling complex vehicle components introduces challenges, such as representing fluid-structure and trim interactions, with spatially varying trim thicknesses. This study presents an industrial application implementing the Virtual SEA (Statistical Energy Analysis) method to evaluate TL for a firewall. The study discusses strategies for subsystem adaptation and analytical trim modeling, highlighting the importance of managing spatial averaging effects. The proposed workflow integrates laboratory measurements of trim materials, advanced subsystem definition, diffuse sound field (DSF) excitation and radiation in free-field condition. Virtual SEA results are systematically validated against
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
The payload fairing of a launch vehicle is subjected to extremely high acoustic loads, with peak levels occurring during lift-off and transonic aerodynamic regimes. The external acoustic field penetrates the fairing, producing intense internal sound pressure levels that can challenge the integrity of spacecraft components. Accurate characterization of the vibroacoustic behavior of the payload fairing and its enclosed cavity is therefore essential to ensure spacecraft survivability. The internal acoustic field is governed by the coupled dynamics of the fairing structure and the spacecraft configuration, making it critical to quantify the acoustic environment for different payload arrangements. This study presents a detailed vibroacoustic analysis of a payload fairing with multiple spacecraft configurations to evaluate the resulting internal sound pressure distribution. Vibroacoustic finite element analysis is employed in the low frequency range, while statistical energy analysis is
Gaganyaan is an ambitious and recover safety mission for the Indian space program to launch humans into space. The success of the mission depends on the development of required technology and systems. A test vehicle is developed for the technological demonstration for all envisioned abort flight scenarios of Gaganyaan mission. A new configuration of launch vehicle with single liquid stage is planned for multiple flights. Coupled Loads analysis of launch vehicle system is a standard practice to estimate response and loads for the design of structures and generating sine vibration test levels. Usually a vehicle rests on the launch pad through base shroud with horizontal support and no vertical restraint. Upon ignition of the engine, thrust builds up and upon overcoming gravity the vehicle takes off. In the current analysis the launch vehicle is held in position using a holding / retracting mechanism and at a predefined time the vehicle is released. The boundary condition required a novel
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