Search Results (21)

The rapid electrification of road vehicles has fundamentally reshaped the priorities of noise, vibration, and harshness (NVH) engineering. In the absence of combustion-related broadband masking, tonal and order-related phenomena originating from the electric machine, inverter switching, and high-speed reduction gearing have become clearly perceptible and, in many cases, acoustically dominant. Consequently, drivetrain noise in electric vehicles can no longer be assessed at component level alone; it must be understood as a coupled system response shaped by excitation mechanisms, structural dynamics, transfer paths, radiation efficiency, and ultimately human perception. This review adopts a source-to-perception perspective and consolidates the principal physical mechanisms governing vibro-acoustic behavior in integrated electric drive units. Electromagnetic force harmonics and torque ripple are discussed alongside transmission-error-driven gear mesh excitation, while bearing and shaft nonlinearities are examined in the context of high-speed operation. In addition, ancillary thermoacoustic and aerodynamic contributions are considered, reflecting the increasingly integrated packaging of modern e-axle architectures. On this mechanism-oriented basis, dominant excitation types are linked to frequency-appropriate modeling strategies, spanning electromagnetic force extraction, multibody drivetrain simulation, structural finite element analysis, transfer path analysis, and acoustic radiation prediction. Particular attention is given to workflow integration across domains. Finally, the paper identifies research challenges that predominantly arise at system level, including multi-source interaction effects, installation-dependent transfer-path variability, emergent resonances in assembled structures, manufacturing-induced tonal artifacts, and the still limited correlation between predicted vibration fields and perceived sound quality. Full article

Long-wavelength flank waviness plays a critical role in the excitation behavior of geared transmissions. While coordinate measuring machine (CMM) exports provide detailed geometric information, conventional evaluations typically focus on individual tooth curves and do not quantify circumferential inhomogeneity across teeth. This study introduces a tooth-to-tooth long-wavelength waviness inhomogeneity indicator (ΔW1) derived directly from Klingelnberg-style MKA plot files and demonstrates its behavior on a large industrial dataset comprising 3375 measured gear parts. Each flank curve was detrended using a second-order polynomial fit, and lobe-based waviness amplitudes (W1–W3) were extracted via sine–cosine projection. The proposed ΔW1 metric was defined as the difference between the maximum and minimum W1 values across measured teeth within the same part. To eliminate measurement edge effects, a mid-section evaluation (10–90% of the face width) was additionally performed. Population-level analysis revealed consistent separation between geometrically homogeneous and inhomogeneous parts, with ΔW1 values in the most critical components exceeding 7–9 µm after mid-section filtering. Unsupervised clustering based on ΔW1 and maximum W1 further distinguished a high-variability subset of parts exhibiting systematic long-wavelength modulation patterns. The results demonstrate that circumferential waviness variability can be quantified using standard CMM outputs without additional hardware or specialized measurement procedures. The proposed indicator provides a practical geometric screening tool for large production batches and establishes a reproducible framework for linking detailed flank geometry to manufacturing consistency assessment. Although acoustic validation is outside the scope of the present work, the metric is intended as an NVH-relevant geometric risk indicator for future vibroacoustic correlation studies. Full article

This study employed an integrated experimental–computational methodology to investigate the critical role of the layer-stacking sequence in the acoustic performance of multi-layer porous materials for vehicle NVH applications. The acoustic properties of four distinct single-layer materials were first characterized via impedance tube measurements. A finite element simulation model based on the Johnson–Champoux–Allard (JCA) theory was subsequently developed in COMSOL Multiphysics 6.2 and rigorously validated. Leveraging this validated model, a systematic analysis was conducted on six different layer sequences under a fixed total thickness of 30 mm. The simulation results showed excellent agreement with experimental data, with a root-mean-square error (RMSE) below 5%. It was demonstrated that the stacking sequence significantly governed the mid-to-high frequency sound absorption behavior, which was strongly correlated with the modulation of the real and imaginary parts of the normalized surface acoustic impedance. This study thus demonstrated that the layer sequence—a previously underexplored design factor—critically determines the absorption performance of multi-layer materials at a fixed total thickness. A full design-space analysis revealed that performance shifts are governed by changes in interfacial acoustic impedance. This physics-driven insight provides a practical framework for tailoring absorbers to specific frequency bands, offering a viable path toward lightweight acoustic solutions for electric vehicle applications. Full article

The global transition from internal combustion engines (ICEs) to hybrid (HEVs) and electric vehicles (EVs) is fundamentally reshaping lubricant design requirements, driven by evolving thermal demands, electrical constraints, and material compatibility challenges. Conventional ICE lubricants are primarily formulated to withstand high operating temperatures, mechanical stresses, and combustion-derived contaminants through established additive chemistries such as zinc dialkyldithiophosphate (ZDDP), with thermal stability and wear protection as dominant considerations. In contrast, HEV lubricants must accommodate frequent start–stop operation, pronounced thermal cycling, and fuel dilution while maintaining performance across coupled mechanical and electrical subsystems. EV lubricants represent a paradigm shift, where requirements extend beyond tribological protection to include electrical insulation and conductivity control, thermal management of electric motors and battery systems, and compatibility with copper windings, polymers, elastomers, and advanced coatings, alongside mitigation of noise, vibration, and harshness (NVH). This review critically examines lubricant behavior, formulation strategies, and performance requirements across ICE, HEV, and EV powertrains, with specific emphasis on heat transfer, electrical performance, and lubricant–material interactions, covering mineral, synthetic, and bio-based fluids. Additionally, regulatory drivers, sustainability considerations, and emerging innovations such as nano-additives, multifunctional and smart lubricants, and AI-assisted formulation are discussed. By integrating recent research into industrial practice, this work highlights the increasingly interdisciplinary role of tribology in enabling efficient, durable, and sustainable mobility for next-generation automotive systems. Full article

Quiet drivetrains have become a central requirement in modern electric vehicles, where the absence of engine masking makes even subtle gear tones clearly audible. As a result, manufacturers are looking for more reliable ways to understand how design choices, manufacturing variability, and operating conditions shape gear noise and vibration. Digital Twin (DT) approaches—linking high-fidelity models with measured data throughout the product lifecycle—offer a potential route to achieve this, but their use in gear NVH is still emerging. This review examines recent work from the past decade on DT concepts applied to gears and drivetrain NVH, drawing together advances in simulation, metrology, sensing, and data exchange standards. The survey shows that several building blocks of an NVH-oriented twin already exist, yet they are rarely combined into an end-to-end workflow. Clear gaps remain. Current models still struggle with high-frequency behavior. Real-time operation is also limited. Manufacturing and test data are often disconnected from simulations. Validation practices lack consistent NVH metrics. Hybrid and surrogate modeling methods are used only to a limited extent. The sustainability benefits of reducing prototypes are rarely quantified. These gaps define the research directions needed to make DTs a practical tool for future gear NVH development. A research Gap Map is presented, categorizing these gaps and their impact. For each gap, we propose actionable future directions—from multiscale “hybrid twins” that merge test data with simulations, to benchmark datasets and standards for DT NVH validation. Closing these gaps will enable more reliable gear DTs that reduce development costs, improve acoustic quality, and support sustainable, data-driven NVH optimization. Full article

The premium electric-vehicle market demands exceptionally quiet transmissions because the absence of engine masking makes gearbox noise more perceptible. Virtual NVH (noise, vibration, and harshness) evaluation requires coupling elastic deformation, gear–tooth contact, and vibration transmission through bearings and housing within a single environment. This study develops an integrated workflow in MSC ADAMS for predicting the NVH behavior of a 23/81-tooth helical gear pair. Finite element-based flank stiffness is imported, and a nonlinear contact model is applied to flexible teeth. Baseline simulation at 50 Nm and 200 rpm yields a static transmission error (TE) of 7.5 µm and a dynamic peak-to-peak TE of 0.7 µm, with the fundamental mesh tone at 77 Hz. Increasing tip relief by +0.10 mm lowers RMS TE by 31% and the first mesh order by 3.1 dB while raising the flank pressure from 1.65 GPa to 1.88 GPa. The workflow efficiently supports early-stage gear-noise optimization prior to the development of physical prototypes. Full article

In comparison to internal combustion engines, which usually have low frequency, broadband excitations, in electric vehicles, tonal excitations from the electric drivetrain are noticeable and disturbing. As the acoustic and structural dynamic behavior, often referred to as noise, vibration, and harshness (NVH), strongly influences customers’ quality perceptions, optimizing it is a key challenge in development. This study investigates the influence of static rotor–stator eccentricity on the NVH behavior of an electric drivetrain using a transient elastic multibody simulation (eMBS) model incorporating non-linear gear meshing, bearing contact, and electromagnetic forces. The analysis identifies the 36th order excitation of the electric machine as the dominant source, leading to a maximum total acceleration level of 152 dB. Two specific excitation directions were found to reduce this amplitude most effectively. However, varying the amount of static eccentricity in these directions resulted in only minor vibration reductions (<1.5 dB). The findings indicate that the symmetric mode shapes of the cylindrical housing govern the response, indicating that addressing the excitability of housing modes by developing asymmetric housing designs could offer a more effective approach for NVH optimizations of electric drivetrains. Full article

Electric vehicle (EV) drivetrains operate at high rotational speeds, which makes the noise, vibration, and harshness (NVH) performance of gear transmissions a critical design factor. Without the masking effect of an internal combustion engine, gear whine can become a prominent source of passenger discomfort. This paper provides the first comprehensive review focused specifically on gear tooth surface waviness, a subtle manufacturing-induced deviation that can excite tonal noise. Periodic, micron-scale undulations caused by finishing processes such as grinding may generate non-meshing frequency “ghost orders,” leading to tonal complaints even in high-quality gears. The article compares finishing technologies including honing and superfinishing, showing their influence on waviness and acoustic behavior. It also summarizes modern waviness detection techniques, from single-flank rolling tests to optical scanning systems, and highlights data-driven predictive approaches using machine learning. Industrial case studies illustrate the practical challenges of managing waviness, while recent proposals such as controlled surface texturing are also discussed. The review identifies gaps in current research: (i) the lack of standardized waviness metrics for consistent comparison across studies; (ii) the limited validation of digital twin approaches against measured data; and (iii) the insufficient integration of machine learning with physics-based models. Addressing these gaps will be essential for linking surface finish specifications with NVH performance, reducing development costs, and improving passenger comfort in EV transmissions. Full article

In electrified vehicles, the masking noise behavior of internal combustion engines is absent, making the tonal excitation of the electric machine particularly noticeable in vehicle acoustics, which is perceived as disturbing by consumers. Due to manufacturing tolerances, the tonal NVH characteristics of the electric machine are significantly influenced at wide frequency ranges. This paper presents a systematic exploration of the influence of static eccentricity as one manufacturing tolerance on the NVH behavior of Permanent Magnet Synchronous Machines (PMSMs). The study utilizes a novel test bench setup enabling isolated variations in static eccentricity of up to 0.2 mm in one PMSM. Comparative analysis of acceleration signals reveals significant variations in the dominance of excitation orders with different eccentricity states, impacting critical operating points and dominant frequency rages of the electric machine. Despite experimentation, no linear correlation is observed between increased eccentricity and changes in acceleration behavior. Manufacturing eccentricity and deviations in rotor magnetization are discussed as potential contributors to the observed effects. The findings emphasize static eccentricity as a critical parameter in NVH optimization, particularly in electrified powertrains. However, the results indicate that further investigations are needed to explore the influence of eccentricities and magnetization deviations on NVH behavior comprehensively. Full article

This study examines the management of noise, vibration, and harshness (NVH) in electric vehicle (EV) powertrains, considering the challenges of the automotive industry’s transition to electric drivetrains. The growing popularity of electric vehicles brings new NVH challenges as the lack of internal combustion engine noise makes drivetrain noise more prominent. The key to managing NVH in electric vehicle powertrains is understanding the noise from electric motors, inverters, and gear systems. Noise from electric motors, mainly resulting from electromagnetic forces and high-frequency noise generated by inverters, significantly impacts overall NVH performance. This article details sources of mechanical noise and vibration, including gear defects in gear systems and shaft imbalances. The methods presented in the publication include simulation and modeling techniques that help identify and solve NVH difficulties. Tools like multi-body dynamics, the finite element method, and multi-domain simulation are crucial for understanding the dynamic behavior of complex systems. With the support of simulations, engineers can predict noise and vibration challenges and develop effective solutions during the design phase. This study emphasizes the importance of a system-level approach in NVH management, where the entire drivetrain is modeled and analyzed together, not just individual components. Full article

Interior permanent magnet (IPM) motors in traction applications often employ discrete rotor skewing constructions to reduce torsional excitations and back-EMF harmonics. Although skewing is very effective in reducing cogging torque, the impact on torque ripple is not well understood and can vary significantly over the operating envelope of a motor. Skewing also leads to the creation of a non-zero axial force that may compromise the bearing life if not considered. This paper introduces a holistic methodology for analyzing the effect of skewing, aiming to minimize torsional excitations, axial forces and back-EMF harmonics whilst mitigating the impact on performance and costs. Firstly, analytical models are employed for calculating cogging torque, torque ripple and axial forces. Then, 2D and 3D finite element analysis are used to incorporate the influence of non-linear material behavior. A detailed structural model of the powertrain is employed to calculate the radiated noise and identify key areas allowing a motor designer to reduce noise, vibration and harshness (NVH). A meticulous selection process for the skewing angle, the number of skew stacks and the orientation of skew stacks is developed, giving particular attention to the effect of the selected pattern on NVH in both forward and reverse rotating directions. Full article

Brake squeal—an audible high-frequency noise phenomenon in the range between 1 kHz and 15 kHz resulting from self-excited vibrations—is one of the main cost drivers while developing brake systems. Increasing damping is often a crucial factor in the context of self-excited vibrations. Countermeasures applied for preventing brake squeal have been investigated particularly for disk brakes in the past. However, in recent years, drum brakes have once again become more important, partly because of the issue of particle emissions. Concerning noise problems, drum brakes have a decisive advantage compared to disk brake systems in that the outer drum surface is freely accessible for applying damping devices. This paper focuses on the fundamental proving and evaluation of passive damping measures on a simplex drum brake system. To obtain a detailed understanding of the influence of additional damping on the squealing behavior of drum brakes, extensive experimental investigations are performed on a brake with an intentionally introduced high squealing tendency in the initial configuration. This made it possible to investigate the influence of different types of damping measures on their effectiveness. Techniques from the field of big data analysis and machine learning are tested to detect squeal in measured time series data. These techniques were remarkably reliable and made it possible to detect squeal efficiently even in data that was not generated on a traditional costly NVH brake dynamometer. To investigate whether the simulation method usually used for the simulation of brake squeal is applicable to depicting the influence of additional damping in drum brakes, a complex eigenvalue analysis was performed with Abaqus, and the results were compared with those from the experiments. Full article

The driving comfort and safety of the automotive powertrain are significantly related to the performance, lifetime, and functionality of the lubricant. The presented study focuses on investigating the performance loss of the lubricant due to water contamination resulting from environmental influences and iron particles originating from the wear of different machine elements. The main purpose is to determine critical factors that contribute to the degradation of the lubricant, and increase the tendency to NVH behavior, leading to adverse comfort losses to the respective user. Therefore, this performance loss is evaluated by test rig-based analysis of the friction behavior of wet clutches. Due to physical adsorption, a significant impact of water and iron contamination on the degradation of the lubricant is found, while the influence of the energy input is secondary. Full article

The increasing use of composite materials in the automotive field requires more attention with regards to the appearance of noise, vibration and harshness (NVH) study in cars construction. However, in car door panels production, impact characteristics need to be evaluated in sandwich laminates. Furthermore, it is important to consider the effect of prolonged environmental aging on crashworthiness properties. The innovative content of the work is the hygrothermal effects evaluation on impact performance for two damped CFRP sandwich laminates. In this paper, two damping materials, Kraibon HHZ9578/99 and SUT9609/24, were used as core between two skins of CFRP for sandwich composite production. Freeze-Thaw aging treatment according to IEC 60068, specific for Automotive, was performed to investigate environmental effects on components. Up to 750 h, it was demonstrated that water absorption is regulated by Fick’s Law. The low-velocity impact behavior of the damped sandwiches has been studied according to ASTM D7136 throughout drop dart test equipment. Both main peak forces and energy absorption characteristics are negatively affected by aging condition. The introduction of damping core inside the composite structure of vehicle components can satisfy NVH constrictions. By contrast, at least same operating conditions must be assured in relation to not-damped components. Full article

In this paper, an analysis of noise and vibration of a synchronous reluctance machine for EV applications is performed. The analyzed machine was designed for electric vehicle application. The noise and vibration of a synchronous reluctance machine were first estimated during simulations; next, the obtained results were validated during laboratory tests. The analyzed model of the machine was simplified and included only stator core as it was assumed to be the main source of the machine vibration and generated noise. To simulate the noise and vibration of the machine, multiphysics modeling of the machine was performed. Laboratory tests proved the correctness of performed simulations. The obtained results allowed us to investigate the influence of the machine’s operating point on the generated noise and vibration. The frequency of the magnetic radial forces were proven to be the dominant factor in noise generation. The influence of the load and current angle on the machine’s noise and vibration was proven to be negligible. It was also proven that considering only the stator structure in numerical analysis of the noise and vibration of the machine leads to valuable results. Full article