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

Items (9,697)
In order to improve the comfort performance in commercial vehicles, this study proposes a hierarchical control strategy that integrates the evaluation and migration of control algorithms. First, a quarter-vehicle model with four-degree-of-freedom (4-DOF) is constructed, incorporating the dynamics of the wheel, frame, driver’s cab, and seat. The key modal characteristics of the model are then verified through amplitude–frequency analysis, confirming their consistency with the typical vibration patterns observed in actual commercial vehicles, which provides the foundation for subsequent control strategy evaluation and migration. Then, based on a standard two-degree-of-freedom (2-DOF) suspension model, a weighted comprehensive evaluation function is developed to account for comfort, structural safety, handling stability, and both time- and frequency-domain performance indicators. Using this evaluation function, various control algorithms—including Skyhook control (SH), acceleration-based
Pan, TingPang, JianzhongWu, JinglaiZhang, JiuxiangKang, GongZhang, Yunqing
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
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
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
Tuned Mass Dampers (TMDs) are widely used in the automotive industry to mitigate Noise, Vibration, and Harshness (NVH) issues across various vehicle systems. These passive devices are particularly effective in reducing structural vibrations in components subjected to resonant excitation. However, real-world applications often face challenges due to manufacturing variability and system-level build differences, which can cause deviations in both the TMD’s tuned frequency (up to ±15%) and the vibration characteristics of the host structure. These uncertainties—in both the TMD properties and the vehicle subsystem dynamics—can be modeled using statistical distributions. This paper presents a generalized methodology for vibration analysis and design under uncertainty, combining reliability engineering with dynamic vibration modeling. The approach formulates a unified mathematical framework that incorporates probabilistic and stochastic modeling to assess TMD performance under a range of
Abbas, AhmadHaider, Syedd'Souza, Suneel
When a vehicle performs planar motion, the tire side force induces a jacking-up effect determined by the suspension roll center height governed by suspension geometry. These jacking forces also excite pitching motion. In this study, the pitching degree of freedom, along with roll degree of freedom, was incorporated in the bicycle model of the vehicle motion, hence it becomes four-degree-of-freedom model, and a new analytical method that applies modal analysis method to the model decomposes the motion of the sprung mass of the vehicle into mutually independent vibration modes. Since the superposition of these vibration modes can reproduce vehicle motion, these vibration modes are the fundamental factors governing sprung-mass behavior. Therefore, understanding how these vibration modes respond to design parameters provides a theoretical foundation to design desired vehicle dynamics from the early stage of car development. This report presents, by conducting modal analysis of the four
Kusaka, KaoruYuhara, TakahiroKoakutsu, Shingo
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
Conventional inverter control uses a fixed switching frequency, which leads to high-pitched switching noise in electric vehicles (EVs) that does not vary with vehicle speed. Although EVs are much quieter than traditional internal combustion engine (ICE) vehicles, some EV owners complain about the lack of dynamic driving sound feedback. A new patented technology has been developed to enhance EV sound quality by dynamically controlling the inverter switching frequencies. This technology generates dynamic propulsion sound with new "switching order" features at multiple harmonics, with the pitch proportional to vehicle speed. A constant pulse ratio between the switching frequency and the electric motor RPM is implemented to control the switching order. This reduces switching losses during low-speed operation and provides boosted acoustic feedback to the driver during acceleration, which enhances driving experience during sports driving. Furthermore, a special "EV shifting" sound that
He, SongGagas, BrentWelchko, BrianBall, KerrieGong, Cheng
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
Resilient mounts are critical in controlling vibration transfer from sources such as engines, motors, and suspension to the vehicle structure. Conventional optimization methods rely on finite element analysis (FEA), which, while accurate, is computationally intensive and limits iterative NVH development. This paper introduces a Frequency Response Function Substructuring (FBS)-based approach that decomposes the system into substructures characterized by FRFs, significantly reducing computational cost without compromising accuracy. Key contributions include: (1) recovering subsystem FRFs from coupled system data in-situ for mount optimization, (2) extending FBS to handle enforced motion, and (3) proposing an alternative strategy for cases with unknown or unmeasurable loads. The methodology is demonstrated on a mid-size pickup truck model to optimize seat track response under a Four post shake load by refining body mounts. These advances broaden the applicability of FBS for efficient NVH
Haider, SyedAbbas, AhmadJahangir, YawarMaddali, Ramakanth
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
Accurate detection and evaluation of kissing bonds in composite materials is essential to ensure the integrity of the component structure, but traditional NDT (non-destructive testing) methods struggle to identify imperfect bonds and zero-volume debonds. In this study, a vibration analysis method based on holography was applied to detect kissing bonds by monitoring the changes in natural frequencies of the same sample before and after fatigue loading. Both pristine and kissing bond samples were tested under identical conditions, and their vibration characteristics (natural frequency, amplitude, and mode shape) were measured using holography. The experimental results show for the intact sample exhibited no changes in natural frequency amplitude or mode shape after fatigue loading, confirming that the applied fatigue test did not affect the integrity of its adhesive layer. In contrast, for the sample with a kissing bond, after fatigue loading, the natural frequency decreased by up to 22
Gao, ZhongfangFang, SiyuanGerini-Romagnoli, MarcoYang, Lianxiang
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
This study investigates the influence of glue coverage and stacking factors on the effective macroscopic mechanical properties of dot-glue adhesively laminated stator cores and the impact of these manufacturing-related attributes on the motor and the electric drive system's structural performance, particularly in terms of noise, vibration, and harshness (NVH). A homogenization framework based on the unit-cell method was developed to model glue-laminated stacks as orthotropic materials suitable for finite-element analysis (FEA) of partially bonded cores. Also, a closed-form analytical solution is proposed to predict the macro-mechanical properties of a core composed of isotropic constituents with the consideration of glue coverage. The approach enables systematic quantification of variations in glue coverage and stacking factor to predict the effective in-plane and out-of-plane elastic and shear moduli of the stator core. For modeling simplicity, glue is assumed to be uniformly
Nie, Zifeng
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
A single-speed electric drive unit (eDU) with multi-stage reduction can have high gear whine due to high pitch-line velocity in the absence of engine masking noise. A comprehensive investigation is conducted focusing on the optimization of the first-stage transfer gear blanks to improve NVH performance and reduce mass for EV applications. A multibody dynamic model of the eDU is constructed, incorporating asymmetric gear blank geometry, shaft elasticity, bearing stiffness, and housing flexibility, to characterize realistic operating conditions and simulate gear contact mechanics with high fidelity and computational efficiency. NVH excitation sources, including static transmission error and dynamic meshing force, are systematically evaluated for solid and slotted gear configurations. Based on a DOE optimization study, an 8-slot gear blank design is selected to balance mass reduction, stress, NVH, and manufacturing requirements. Micro-geometry optimization is conducted for the slotted
He, SongDu, IsaacLi, BoBahk, CheonjaeGrguras, ZacharyBaladhandapani, DhanasekarPatruni, Pavan Kumar
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
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
In the current field of rolling bearing fault diagnosis, two critical challenges persist. First, it is difficult to effectively extract fault features from nonlinear and non-stationary vibration signals. Second, precise diagnosis remains a challenge, especially when distinguishing between different fault types and capturing incipient faults with weak characteristic information. To address these issues, this paper proposes a novel fault diagnosis method based on adaptively optimized variational mode decomposition (VMD) and deep temporal fusion. First, the method improves the traditional sparrow search algorithm (SSA). It enhances SSA’s global optimization capability through strategies like chaotic population initialization and adaptive perturbation. This improved SSA enables efficient global optimization of VMD’s key parameters. Leveraging these optimized parameters, the method decomposes modal signal components with different center frequencies from the vibration signal. This process
Wen, ChaoZhong, HongWang, LiangmoChen, YongGao, QiangLi, Yong
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
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
As already well-understood/enormous engineering practices, the inverter AC-side NVH phenomena/mechanisms/measures for motor-equipped vehicle, are already pretty clear. In addition to inverter AC side–induced NVH issues, DC ripple induced by PE switching leads to NVH issues manifesting on the capacitor, inductor, and conductor in terms of reverse piezoelectricity, electrostriction, magnetostriction, Laplace force, and so forth. These DC-side NVH issues are already literally analyzed by a couple of literatures, and mechanisms/measures are explored/applied to electric drive development. And yet, the phenomenon that a pulsating magnetic field inside a battery pack induced by DC current ripple off PE switching brings noise at switching frequency inside the vehicle cabin is newly captured/analyzed by our research, and that has been barely searched during the literature survey. This newly discovered phenomenon is the pivotal point in this paper. Although the noise features like the
Zhao, QianZhao, YihanNiu, HaolongLi, QiweiZhang, WenchaoXue, HongbinCheng, YananLi, JingKang, Ming
Limited published research has critically examined the impact of Cell-to-Chassis (CTC) structures on the Noise, Vibration, and Harshness (NVH) performance of electric vehicles (EVs), with most studies focusing on conventional Cell-to-Pack (CTP) systems. A concern is that vehicles employing CTC architectures may exhibit compromised NVH performance due to the absence of a dedicated floor panel. To investigate the NVH performance implications of the CTC structure, this study adopts a comprehensive methodology encompassing: (1) theoretical Sound Transmission Loss (STL) analysis utilizing mass law and double-panel principles, (2) finite element (FE) modeling of STL, (3) in-vehicle Acoustic Transfer Function (ATF) testing, and (4) interior noise measurements conducted at a constant 60 km/h on a smooth asphalt road. Simulation results demonstrate that, compared to a conventional CTP floor system, the studied CTC structure achieves a 5–40 dB increase in STL across the 200–2000 Hz frequency
Xu, XueyingWang, XiaomingMa, CaijunLi, Guofu
This study investigates the effect of liquid-applied spray damping (LASD) thickness on the vibration and sound radiation of thin steel panels. Although LASD is widely used to enhance structural damping, its influence on radiated sound and the role of coating thickness have not been systematically studied. Five steel panels with varying LASD thicknesses were evaluated using two experimental approaches. An impact-based method in a hemi-anechoic chamber measured the structural mobility and noise transfer functions, while a reciprocal method in a reverberation chamber under acoustic excitation measured the radiated sound power transfer function. A thickness ratio was found beyond which additional LASD thickness yielded diminishing improvements in noise and vibration reductions. The effect of LASD thickness on radiation efficiency was also assessed in both narrowband and one-third octave bands.
Neihguk, DavidSuh, SamHerrin, David W.
In commercial vehicles, Hydraulic Power Assisted Steering (HPAS) gear plays a crucial role in enhancing steering performance by providing hydraulic assistance. The HPAS gear comprises a Directional Control Valve (DCV) assembly, where the input shaft and recirculation units are integrated. The valve system which is known for the heart of the HPAS gear, operates under high-pressure conditions. In the DCV, the input shaft is equipped with bearings to support side loads exerted by the system, and a valve component is freely assembled to minimize friction caused by these side loads. The complexity of the floating valve design results in the less slot volume, leading to cavitation and vibrational noise. While this noise is typically suppressed in internal combustion (IC) engine-powered vehicles, its implementation in electric vehicles (EVs) has led to pronounced audible noise, dominating the system. Experimental vibration analysis of the steering gear reveals both low and high-frequency
Vijayenthran, PraveenAyyappan, RakshnaD, Senthil KumarN, Prabhakar
Internal combustion engines generate intense acoustic pulses during combustion, necessitating the use of exhaust mufflers to suppress noise emissions. With evolving regulations on permissible noise levels and the automotive industry's drive toward lightweight, high-performance vehicles, muffler designs must balance effective sound attenuation, minimal back pressure, and reduced mass. This study presents a comparative analysis of three muffler configurations serpentine, rectangular, and zigzag designed using Solid Works for a light commercial vehicle (LCV) diesel engine. The models were evaluated using computational fluid dynamics (CFD) simulations to assess their acoustic and flow performance. Each design incorporated internal baffle arrangements to enhance sound absorption while aiming to minimize back pressure. The serpentine model featured a perforated baffle layout that promoted multiple reflections and dissipated acoustic energy more efficiently. Simulation results indicated that
Deepan Kumar, SadhasivamPalaniselvam, Senthil KumarD, AshokkumarR, KrishnamoorthyMahendran, MPasupuleti, ThejasreeG, DhayanithiL, Boopalan
In the automotive industry, increasing noise regulations are influencing product sales and passenger comfort, creating a need for more effective noise testing methods. Hardware-in-Loop (HiL) based virtual acoustic testing serves as a critical step before Driver-in-Loop testing, allowing for the assessment of vehicle performance and noise levels inside and outside the vehicle under various conditions before physical prototype testing is performed. The Hardware-in-the-Loop (HiL) simulator setup is equipped with joystick control that requires a physical representation of the vehicle dynamics model provided as a Functional Mock-up Unit (FMU) in real-time format. In contrast, the vehicle control logic is implemented in C++ code. The simulator incorporates both lateral and longitudinal dynamics. Additional interfaces are integrated to support joystick input and virtual road visualization enabling realistic vehicle maneuvering and dynamic performance evaluation. However, performing all test
Visuvamithiran, RishikesanChougule, SourabhSrinivasan, RangarajanLaurent, Nicolas
This study presents a comparative investigation of the vibration characteristics of rectangular and circular plates with fixed edges using analytical, numerical, and computational approaches. Analytical models based on classical plate theory were employed to calculate natural frequencies and mode shapes, while finite element analysis (FEA) was performed in a CAE tool to provide high-fidelity simulation results. A detailed mesh convergence study confirmed numerical stability, with frequency variations below 1% between successive refinements. Analytical predictions showed excellent agreement with simulation results for lower modes, with errors as low as 0.25% for the rectangular plate and 2.65% for the circular plate. However, higher modes exhibited significant deviations, with errors reaching up to 29.01% for rectangular and 181.52% for circular geometries, highlighting the limitations of closed-form solutions in capturing complex vibrational behavior. Python-based computational tools
N, SuhasR, SanjayBhaskara Rao, Lokavarapu
As internal combustion engines are replaced by quieter electric motors in ground vehicles, noise and vibration sources aside from the powertrain have become relatively more important. This is especially true of tires. Measurement of the dynamic vibratory characteristics of tires is critical to understanding their influence on the noise and vibration performance of vehicles, both outside the vehicle body and inside of it. In this work, the normal modes and operating deflection shapes of a Yokohama Geolander A/T light truck tire are measured using traditional modal analysis techniques as well as a non-contact Scanning Laser Doppler Vibrometry (SLDV) approach. Boundary conditions including free, fixed, loaded, and rotating are implemented to the tire and investigated. Rotating conditions are accomplished in a physical chassis dynamometer environment, with the measured tire mounted on the front axle of a Chevrolet Silverado 1500 pickup truck. Modes of vibration and associated natural
Bastiaan, Jennifer M.Chauda, GauravBaqersad, JavadGupta, ArjunDhami, Kevalya
The vibrating half-car model is used to represent the dynamic behavior of a truck’s dependent suspension system, capturing four degrees of freedom. This research investigates time and frequency responses of vibration behavior of half-car model with possible tire–road separation. This investigation is significant because all previously reported analyses based on the tire-road attachment were incorrect, particularly regarding the tire-road separation phenomenon. The differential equations are extended to enhance the accuracy of the model, incorporating tire–road separation conditions for both wheels. A numerical approach is applied to simulate the vertical and roll dynamics of the system under the separation assumption. The simulation results are validated through experiments conducted using ADAMS View software. Integrating the tire–road separation into the model results in dynamic responses that closely reflect real-world behavior. These findings provide valuable guidance for designing
Nguyen, Quy DangJazar, Reza
This study investigates noise, vibration, and harshness (NVH) characteristics of hydraulic steering systems in medium- and heavy-duty commercial vehicles due to hydraulic system design. Utilizing on-vehicle and lab environment testing, primarily a pressure sweep test and speed sweep test, to identify sources of NVH. Testing demonstrated a significant impact to perceptible noise and vibration through changes to system and component design. NVH mitigation is accomplished by reducing pressure pulsations, cavitation, and turbulence within the fluid by changing hydraulic plumbing diameter. Reduction in sound pressure level (SPL) averaged 30% with peak reduction of 75%. While optimizing hose diameter is an effective method for controlling NVH in commercial vehicle hydraulic steering systems, additional studies should be conducted in optimizing plumbing materials and routing.
Bari, Praful RajendraKintner, Jason
Window glass is a component of the side door assembly of cars. It provides a clear vision for passengers and outsiders. It functions as a temporary opening and ventilation system for the car. It is a part of a car’s aesthetics; it adds stiffness to the door and protects the occupants from different weather conditions. The objectives of this study were to understand the effect of fully and partially opened or closed window glass on the dynamic behaviors of door assemblies and to develop a process to assess these dynamic behaviors. An assessment methodology was developed to determine the effects of various window glass positions on the dynamic behavior of the door assembly. An authenticated finite element (FE) model was used to complete this investigation. The finite element model of the door assembly was validated by correlating the modal frequencies with their corresponding mode shapes. The correlated FE model with the window glass fully closed was called the baseline (W0), and eight
Jadhav, Pandurang MarutiWaghulde, Kishor B.Bhortake, Rupesh V.
Sonar sensor systems have been developed to prevent collisions between vehicles and surrounding objects by employing ultrasonic sensors mounted at the front of the vehicle. These systems warn drivers when nearby obstacles are detected. However, relatively few studies have examined the capacity of sonar to detect humans. This study aims to clarify the human detection capacity of front sonar sensors installed in two light passenger cars (LPC-I and LPC-II), one small passenger car (SPC), and one minivan (MNV). The LPC-I, SPC, and MNV were equipped with center and corner sensors, whereas the LPC-II had only corner sensors. Three volunteers—a child, an adult female, and an adult male—participated in the study. Human detectability was assessed using the “maximum detection distance ratio,” defined as the ratio of the maximum detection distance for a volunteer to that for a standard pipe. The results showed that both the center and corner sensors consistently detected front- and side-facing
Matsui, YasuhiroOikawa, Shoko
One can witness the constant development and redevelopment of cities throughout the world. Construction equipment vehicles (CEVs) are commonly used on the construction site. However, the noise pollution from construction sites due to the use of CEV has become a major problem for many cities. The construction equipment employed is one of the main causes of these elevated noise levels. The construction workers face a potential risk to their auditory health and well-being due to the noise levels they are exposed to. Different countries have imposed exterior and operator’s ear noise limits for construction equipment vehicles, enabling them to control noise pollution. In this study, three vehicles were selected and checked for NVH performance and found that the operator ear noise level of the identified vehicle is 6 dB(A) higher than the benchmark vehicle level in dynamic conditions, when tested as per ISO 6396. Similarly, there was another vehicle having exterior noise 2 dB(A) higher than
Shinde, GauravJawale, PradeepJain, SachinkumarHarishchandra Walke, Nagesh
The world is moving towards data driven evolution with wide usage tools & techniques like Artificial Intelligence, Machine Learning, Digital Twin, Cloud Computing etc. In automotive sector, the large amount of data being generated through physical and digital test evaluations. Computer-Aided Engineering (CAE) is one of the highest contributors for data generation as physical testing involves high cost due to prototypes & test set-up. The Automotive Noise, Vibration & Harshness (NVH) field is advancing exponentially due to new stringent regulatory norms & customer preferences towards comfort, where digitally advanced techniques are playing a key role in the revolution of NVH. Data generation through CAE tool is a crucial aspect of Engineer’s daily activities and selecting such appropriate CAE software and solvers is critical, as it influences user interface experience, accuracy, solution time, hardware requirements, variability expertise, Design of Experiments ability, and integration
Hipparge, VinodMasurkar, NikitaArabale, VinandBillade, Dayanand
The present study enumerates the effectiveness of using Foam-inside Tyres (FIT) for attenuating the in-cabin noise due to tire-road interaction in Internal Combustion Engines (ICE) converted Electric SUVs (E-SUV). Due to the elimination of the ICE Prime movers in (E-SUV), the Tyre booming, Tyre cavity, and rumbling noise in the structure-borne region are significantly audible in the driver’s & passenger's ears globally for E-SUVs. Foam tyres reduce tyre cavity resonance. However, the effectiveness of the acoustic foam is predominant between 180 to 240 Hz only. In the present study, In Cabin Noise (ICN) measurement was completed on the comfort testing track, and the results of structure-borne in-cabin noise up to 500 Hz were analysed. These measurements identified the vehicle in-cabin sensitive frequencies, which are affected by the tyre and wheel assembly. To analyse the contribution of the Tyre design parameters and to predict the ICN performance in the whole vehicle simulation, CD
Singh, Ram KrishnanDeivasigamani Purushothaman, BalakrishnanPaua, KetanAhire, ManojAdiga, Ganesh N
Powertrain is the most prominent source of Noise and Vibration in the vehicle. Improvement in Powertrain Noise and Vibration is a multifaceted topic due to the complex architecture of the powertrain and the critical role of calibration in defining combustion inputs. Hence, a method to clearly distinguish these aspects is required in order to address the exact problem and decide on course of actions to improve NVH performance of powertrains. This paper discusses a post-processing technique through which experimentally acquired ICE Powertrain Noise can be further segregated in order to identify and address the root source. The segregation methodology requires as input - noise, vibration and cylinder pressure values at various torque conditions across multiple operating points. A MATLAB based code developed by the authors is used to generate correlation between the Cylinder Pressure, Torque and Noise Parameters. The transfer coefficient at every frequency point is calculated using
K J, KishorKulkarni, ShriramRawat, UdeshyaPisal, SangramNaidu, Sudhakara
With the transition from ICE vehicles to EV’s, the dominant noise sources within the vehicle cabin have shifted from engine noise to auxiliary systems, especially HVAC systems. In conventional vehicles with internal combustion engines (ICE), engine noise tends to mask noise from auxiliary sources. However, in electric vehicles (EVs), the lack of engine noise causes these auxiliary noises, such as those from the HVAC system, to become more prominent and potentially uncomfortable for occupants. The primary objective is to understand how the absence of engine noise in EVs influences the perceived HVAC noises. The research methodology involves static and on-road evaluation of both electric and ICE vehicle having common platform, conducted under same testing conditions. The study aims to quantify and compare the acoustic characteristic differences of HVAC noise between ICEs and EVs, primarily focusing on cabin airflow noise, refrigerant flow noise, and AC compressor noise. Based on the
Patra, SubhashreeJoshi, RishiSharma, RachitLingampelly, RajaprasadNeupane, Manoj
This work focuses on the prediction of Trimmed Body Noise Transfer Function (NTF) using Glazed BIW (body in white) structural model characteristics by leveraging Machine Learning (ML) technique. Inputs such as Glazed BIW (GBIW) attachment dynamic stiffness, Body Panel Vibration Transfer Functions (VTF) and Driver Ear level NTFs are employed to predict Trimmed Body NTF for a particular hard point. An iterative process of performing design modifications on the BIW to verify its effect on BIW performance and therefore on Trimmed body NTF is undertaken. BIW geometric parameters are varied in an organized manner to generate hundreds of data points at GBIW level which are provided as input to the train the ML model to predict the trimmed body level NTF. The outcome provides crucial insights of how the trimmed body NTF is closely related to the GBIW design characteristics. This ML approach of predicting trimmed body NTF based on GBIW characteristics provides critical insight about GBIW design
Kulkarni, Prasad RameshBijwe, VilasKulkarni, ShirishSahu, DilipInamdar, Pushpak
In recent decades, Computer-Aided Engineering (CAE) has become increasingly critical in the early stages of vehicle development, particularly for performance improvement and weight optimization. At the core of this advancement lies the accuracy of CAE models, which directly impacts design insights and reliable TEST-CAE correlation. Yet, accurately replicating real-world physical systems in virtual environments remains a significant challenge. This research introduces a structured methodology for improving correlation in door system models. It focuses specifically on reducing glass regulator operating noise, a common design issue that can lead to unwanted sounds and passenger discomfort. Traditional CAE models often fail to predict this problem, exposing the limitations of virtual-only validation. To address this gap, the study proposes a modal correlation-based approach aligned with actual assembly stage conditions. This strategy enables more precise assessment of the glass regulator’s
Panuganti, Naresh KumarChoi, Seungchan
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