Ambrus Zelei

36132592600

Publications - 25

Using Machine Learning Models to Predict and Reduce Noise Levels in Gear Systems

Ambrus Zelei Krisztián Horváth

Publication Name: Advances in Science and Technology

Publication Date: 2025-01-01

Volume: 165 AST

Issue: Unknown

Page Range: 215-221

Description:

Machine learning models are effective tools for predicting and reducing noise levels in industrial gear systems. In this study, we compare different machine learning methods to investigate the effects of different gear modification parameters on noise levels. Four different predictive models was used. Random Forest Regressor, XGBoost, Gradient Boosting Machines and neural network. The study concluded that Random Forest and Gradient Boosting Machines models were the most effective. Both models achieved low mean squared error values 6.10 and 6.67. Further tests with synthetic data confirmed the stability of these models. Current sustainability trends show that the integration of machine learning into industrial applications fits well with manufacturers' objectives. However, it is currently challenging to determine which machine learning methods are most effective in optimizing noise reduction. This paper seeks to address this gap by comparing the accuracy and reliability of these models. Based on the results, the use of machine learning models is recommended to reduce noise levels in geared systems.

Open Access: Yes

DOI: 10.4028/p-0GDArj

In Silico Benchmarking of Fatigue Life Estimation Models for Passive SMD Solder Joints Under Thermal Cycling

Ambrus Zelei Gusztáv Fekete Antal Bakonyi

Publication Name: Applied Mechanics

Publication Date: 2024-12-01

Volume: 5

Issue: 4

Page Range: 877-907

Description:

Related to microelectronics’ reliability, lifetime estimation methods have gained importance, especially for surface-mounted devices. The virtual testing of electronic assemblies necessitates the geometry modeling and finite element analysis of the solder joint. The effect of the simplification of the solder geometry on the predicted lifetime is an open question. Furthermore, there is still not yet straightforward guidance for the choice of the material model and fatigue lifetime model. In this study, the impact of the geometry input method, the material model and the lifetime model choice is investigated on two different surface-mounted capacitors in a simulation-based benchmark analysis under thermal cyclic loading. Four different types of solder geometry modeling approaches are compared, among which one is a physics-based approach. Ten different fatigue models founded on plastic and viscoplastic material models are benchmarked. The results show that the component standoff height and the solder volume have a positive effect on the lifetime, while the capacitor size has a slightly negative effect on the lifetime. The results also suggest that approximate geometries can be used to replace the physics-based model with a restriction for the minimum standoff height.

Open Access: Yes

DOI: 10.3390/applmech5040049

Comparison of feed-forward control strategies for simplified vertical hopping model with intrinsic muscle properties

Ambrus Zelei Dóra Patkó

Publication Name: Bioinspiration and Biomimetics

Publication Date: 2024-11-01

Volume: 19

Issue: 6

Page Range: Unknown

Description:

To analyse walking, running or hopping motions, models with high degrees of freedom are usually used. However simple reductionist models are advantageous within certain limits. In a simple manner, the hopping motion is generally modelled by a spring-mass system, resulting in piecewise smooth dynamics with marginally stable periodic solutions. For a more realistic behaviour, the spring is replaced by a variety of muscle models due to which asymptotically stable periodic motions may occur. The intrinsic properties of the muscle model, i.e. preflexes, are usually taken into account in three complexities—constant, linear and Hill-type. In this paper, we propose a semi-closed form feed-forward control which represents the muscle activation and results in symmetrical hopping motion. The research question is whether hopping motions with symmetric force-time history have advantages over asymmetric ones in two aspects. The first aspect is its applicability for describing human motion. The second aspect is related to robotics where the efficiency is expressed in term of performance measures. The symmetric systems are compared with each other and with those from the literature using performance measures such as hopping height, energetic efficiency, stability of the periodic orbit, and dynamical robustness estimated by the local integrity measure (LIM). The paper also demonstrates that the DynIn MatLab Toolbox that has been developed for the estimation of the LIM of equilibrium points is applicable for periodic orbits.

Open Access: Yes

DOI: 10.1088/1748-3190/ad7345

Development of a multibody model for go-karts considering frame flexibility

Ambrus Zelei Krisztián Horváth

Publication Name: Pollack Periodica

Publication Date: 2024-10-16

Volume: 19

Issue: 3

Page Range: 66-73

Description:

This study focuses on the optimization dynamics of racing go-karts, which is heavily influenced by the frame's stiffness. Lacking suspensions and differentials, go-karts rely on the frame stiffness for wheel balancing and skid prevention by lifting the inner rear wheel during turns. Utilizing a rigid-flexible model in MSC Software ADAMS View, validated by frame deformation measurements, this research integrates finite element analysis with multibody techniques. The model, leverages computer aided design files for frame geometry and employs finite element analysis for frame validation. It facilitates evaluating go-kart dynamics through simulations, aiding in maneuver testing and design optimization. This approach provides a comprehensive framework for advancing go-kart designs.

Open Access: Yes

DOI: 10.1556/606.2024.01050

Simulating Noise, Vibration, and Harshness Advances in Electric Vehicle Powertrains: Strategies and Challenges

Ambrus Zelei Krisztián Horváth

Publication Name: World Electric Vehicle Journal

Publication Date: 2024-08-01

Volume: 15

Issue: 8

Page Range: Unknown

Description:

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.

Open Access: Yes

DOI: 10.3390/wevj15080367

Performance Optimization of a Formula Student Racing Car Using IPG CarMaker—Part 2: Aiding Aerodynamics and Drag Reduction System Package Design †

Ambrus Zelei Dominik Takács

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

Part 1 of this paper summarizes the application of the IPG CarMaker 11.0 software for lap-time simulation and optimization. The goal is to use the IPG CarMaker on a given track for the optimization of the aerodynamics package parameters and the drag reduction system (DRS). The optimal aerodynamic downforce coefficient is determined for a given vehicle. The simulations clearly suggest that the application of the DRS pays off for a Formula Student car, if the DRS activation and deactivation times are chosen carefully. As IPG CarMaker seems to be a powerful tool, the Arrabona Racing Team decided to extend its application.

Open Access: Yes

DOI: 10.3390/engproc2024079077

Performance Optimization of a Formula Student Racing Car Using the IPG CarMaker, Part 1: Lap Time Convergence and Sensitivity Analysis †

Ambrus Zelei Dominik Takács

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

It is increasingly common for simulation and AI tools to aid in the vehicle design process. The IPG CarMaker uses a multibody vehicle model and a learning algorithm for the virtual driver. The goal is to discover the behavior of the learning algorithm from the point of view of reliability and convergence. Simulations demonstrate that the lap time converges reliably. We also report that small changes in the vehicle parameters induce small changes in the simulated lap time, i.e., the lap time is a differentiable function of the vehicle parameters. Part 2 of this paper explains the aerodynamics and Drag Reduction System optimization.

Open Access: Yes

DOI: 10.3390/engproc2024079086

Noise Reduction Methods in the Vehicle Industry: Using Vibroacoustic Simulation for Sustainability

Ambrus Zelei Krisztián Horváth

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 763-768

Description:

To achieve sustainability goals, such as greenhouse gas emissions and environmental noise reduction, continuous innovation plays a key role in the vehicle industry. The noise emitted by vehicles negatively impacts both the environment and public health, making the development of noise reduction strategies crucial. Vibroacoustic simulation methodologies provide an opportunity to optimise vehicle power transmission systems by reducing the emitted noise level. Besides, the energy efficiency and performance of the vehicles can be improved by vibroacoustic simulations. In this research, a vibroacoustic simulation methodology is presented, focusing on the power transmission systems of vehicles. This approach integrates the Finite Element Method and Multibody Dynamics simulations with vibroacoustics to identify and redesign noisy components even during the conceptual design stage. This approach tackles the challenge of high-frequency tonal noise for electric vehicles, using psychoacoustic reviews to enhance passenger comfort. Key tasks involve electromagnetic force analysis in the drivetrain, structural vibration simulations, and noise reduction strategy optimisation using machine learning algorithms to reduce the reliance on physical prototypes. Capturing the current momentum of the industry, machine learning capabilities in vibroacoustic models can help engineers identify sources and eliminate or mitigate noise in the early design phase. Reducing the number of prototypes leads to more sustainable design processes. Our study shows the noise level can be reduced by 3-5 dB. This is particularly important in the context of electric vehicles, where high-frequency tone noise should be reduced, benefiting both passengers and their environment. Improving these factors is in line with the goals of the United Nations and improves the quality of urban life. Our research highlights the importance of vibroacoustic simulation and opens new directions in the field of noise reduction, promoting the spread of sustainable transport solutions.

Open Access: Yes

DOI: 10.3303/CET24114128

Benchmark Analysis of Plastic Strain-Based Lifetime Estimation Fatigue Models in Aspect of SMD Component Standoff Height

Ambrus Zelei Antal Bakonyi

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 128-134

Description:

Thermomechanical fatigue is one of the most common cause of the failure in microelectronic technology in the solder joints. The lifetime prediction for microelectronic components is a very important area in nowadays automotive industry, because the lifetime estimation fatigue models in the literature differ in their results by orders of magnitude. However, developing an accurate lifetime estimation methodology for microelectronic components is not straightforward, because the failure mechanism of the solder joints under cyclic thermomechanical load is not fully understood. In addition, there are numerous tolerances and uncertainties during the designing and manufacturing processes, such as component size, copper pad area, solder material volume or the formed standoff height of the component from the copper pad. These parameters can hugely affect the lifetime of the solder joint. In this paper a benchmark analysis based on finite element method were carried out with four plastic strain-based fatigue models to understand the impact of the standoff height to the estimated lifetimes. Three CAD models were created with identical parameters, except the standoff height of the components. Creating the solder geometries for the 3D models, Surface Evolver software were used. The result shows that the fatigue models give the same tendencies varying the standoff height values. However, changing the standoff height increases the differences between models, even if they are tuned so that the estimated lifetime matches for a certain standoff height.

Open Access: Yes

DOI: 10.3233/ATDE240536

Non-Square Inverse Function Jacobians in Controlled Multibody Systems: Numerical and Application Examples

Ambrus Zelei

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 112-120

Description:

When control algorithms of robots are constructed, the joint coordinates and the coordinates describing the dynamics might be different and the transformation between them might be necessary in both directions. The back-and-forth transformations are related to the inverse function theorem, which is well understood for single and multivariable continuous functions: the conditions are described under which the inverse function exist, furthermore the method is provided to calculate the Jacobian of the inverse function. A generalization of the theorem is necessary, when there are fewer dependent variables than independent ones, and furthermore there are constraint equations for the independent variables. It is exactly the case for model-based inverse dynamics control of multibody systems, when the dynamic model is given in terms of a redundant coordinate set, but the controller is formulated for minimum set coordinates. The widely used so-called natural coordinates are a typical redundant set. Minimum-coordinates come in the picture when the control is formulated for the joint coordinates. Clearly, when the natural coordinates are transformed to joint coordinates, there is information loss. The inverse transformation is however still possible, since there are constraint equations for the redundant set. This paper demonstrates a method for the transformation from minimum to redundant coordinates and vice versa with the help of the generalized inverse of the non-square constraint Jacobian and the projection matrices related to the constrained and admissible subspace of the redundant set. An illustrative numerical example and a robotic application demonstrate the theory. The results are relevant in the model-based control of complex-structure parallel kinematic chain robots.

Open Access: Yes

DOI: 10.3233/ATDE240534

Gearbox Fault Diagnosis Using Industrial Machine Learning Techniques †

Ambrus Zelei Krisztián Horváth

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

This paper highlights the need for precise and reliable diagnostic methods for early fault detection in gearbox systems, something critical for industrial maintenance. Advances in machine learning (ML) and image processing have opened new avenues for diagnosis. This study explores ML techniques, particularly edge detection and maximized pooling, with the Inverse Distance Weighting method, for diagnosing gearbox faults from vibration signal images. Using the ODYSSEE-A Eye platform, a model was developed that achieved 96% accuracy in identifying faults from a 500-sample dataset. The research results promote further investigation and progress in this area, indicating specific possible directions for further research.

Open Access: Yes

DOI: 10.3390/engproc2024079036

Literature Review of Vibroacoustic Simulation in Geared Vehicle Power Transmission Systems for the Reduction of Radiated Noise

Ambrus Zelei Krisztián Horváth

Publication Name: Advances in Science and Technology

Publication Date: 2024-01-01

Volume: 153

Issue: Unknown

Page Range: 89-98

Description:

The radiated noise reduction of vehicular power transmission systems is one of the most actively researched areas. Noise not only impacts the comfort and safety of the driver and passengers but also regulated by the legislators. The simulation-based prediction of radiated noise of gear-drives is a rapidly evolving area and combines gear meshing models, finite element analysis, multibody dynamics and airborne noise simulation tools. The interfacing of these tools makes virtual noise prediction challenging. In this research, we conducted a literature review on vibroacoustic simulations, with a particular focus on reducing noise in power transmission systems. Based on the reviewed articles, it became evident that, although numerous measurement data are available, the usability of the data is limited. Most research focuses on individual stages of the structure and on smaller-sized powertrains. The measurement methods contain abundant valuable information; however, the literature lack of comprehensive articles that track the simulation process from the inception of excitation to body and air noises. Moreover, the majority of articles investigate the relationship between transmission error and NVH, considering it as a primary source of noise. New methodological approaches, such as the application of FEM meshes on gears, open new horizons in this domain. Throughout the literature review, we compiled potential noise-reduction solutions and highlighted directions for future methodology development research.

Open Access: Yes

DOI: 10.4028/p-Ucpx27

Energy-Based Approach on Calculating Stand-Off Height of Different Solder Joints

Ambrus Zelei Antal Bakonyi

Publication Name: 2024 IEEE 10th Electronics System Integration Technology Conference Estc 2024 Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In the lifetime prediction simulations of microelectronics solder joints, the stand-off height and misalignment parameters are founded on a variety of estimation methods from very simple to complex approaches. However, the stand-off height and misalignment play essential role in the lifetime of solder joints. Thus, a reliable lifetime simulation requires proper solder geometry model. Many researchers calculate the solder geometry with the software called Surface Evolver, which minimizes the total energy, including the surface tension energy. Some of these studies used energy-based methods for the stand-off height prediction. The first hypothesis is that by changing the predefined value of stand-off height in the Surface Evolver simulation, we gain different total energy values and by differentiating the energy with respect to the stand-off height, we can obtain the vertical force and a nonlinear spring characteristic for the molten solder. Similar results can be found in the literature for BGA. Secondly, it is hypothesized that this spring-like behaviour is observable in horizontal direction too, which is related with the misalignment of the component. The presented approach provides a simple model for the prediction of the stand-off height and misalignment.

Open Access: Yes

DOI: 10.1109/ESTC60143.2024.10712056

Predicting Natural Frequencies of a Cantilever Using Machine Learning

Ambrus Zelei Krisztián Horváth

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 105-111

Description:

In the context of structural analysis and design, natural frequencies play a vital role, and their prediction is essential in machine and vehicle design processes. The simulations related to the modal parameters are computationally intensive for systems with large complexity. This paper demonstrates on an illustrative academic example that natural frequencies can be successfully predicted using ML models. This paper aims to develop a model based on machine learning (ML) to predict a simple cantilever's natural frequencies based on the physical parameters of the beam. The independent variables X are the geometric parameters including width, length, and thickness, while the dependent variable Y is the natural frequency. The study is framed using a systematic methodology that covers the stages of data collection, ML model selection, model training and validation. The validation process proves the effectiveness of ML as a computationally cheap replacement for traditional methods of prediction. The current research contributes to the investigation of the usage of commercially available ML tools in structural engineering. We report that the ODYSSEE A-Eye software is capable of natural frequency prediction with a varying geometry structure with less than 4% error for an 80-member training set of cantilever beam with various dimensions. Further developments will include considerations of noise, vibration, and harshness (NVH) to enhance system performance and improve user comfort.

Open Access: Yes

DOI: 10.3233/ATDE240533

Sensitivity to Geometric Detail in Fatigue Simulation of Electronic Components of Vehicles †

Ambrus Zelei Zoltán Z. Kovács

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

Solder joints strongly determine the lifetime of electronic components subjected to temperature fluctuations. The lifetime predictions obtained by finite element analysis (FEA) are uncertain due to the significant variation in solder geometry. It is unclear how realistic a geometric model is needed for problems of impartial complexity. A balance must be found between modeling effort and simulation accuracy. Six geometric models of the solder joint of a gullwing lead were built with different complexity, from the simplest to the most realistic, including a realistic reference model obtained by the Surface Evolver simulation software. The FEA results considering linear elastic and plastic material models were compared for the different solder geometries. We conclude that manually created solder geometry is a sufficient alternative to physics-based realistic geometries.

Open Access: Yes

DOI: 10.3390/engproc2024079084

Discovery and Interactive Representation of the Dimensionless Parameter-Space of the Spring-Loaded Inverted Pendulum Model of Legged Locomotion Using Surface Interpolation

Ambrus Zelei Dóra Patkó Ábel Mihály Nagy

Publication Name: Springer Proceedings in Mathematics and Statistics

Publication Date: 2024-01-01

Volume: 454

Issue: Unknown

Page Range: 373-386

Description:

The spring-loaded inverted pendulum is a widely used model of legged locomotion. However, a complete map of the dimensionless parameter regions that correspond to the stable periodic solutions cannot be found in the literature. In this work, the three-dimensional space of two dimensionless physical parameters and the dimensionless total mechanical energy of the conservative system was discovered by means of numerical continuation. The fundament of the stability analysis of the piecewise-smooth system was provided by the numerical calculation of the fundamental solution matrices and the monodromy matrix. An effective iteration procedure based on the Nelder-Mead method is presented which tunes the model parameters in order to imitate the motion characteristics of specific animals and locomotion types such as running, trotting and galloping. The results are available online in the form of an interactive platform.

Open Access: Yes

DOI: 10.1007/978-3-031-56496-3_24

Correlation of Biomechanical Performance Measures with Speed, Acceleration and Deceleration in Human Overground Running

Ambrus Zelei Liliána Zajcsuk

Publication Name: Springer Proceedings in Mathematics and Statistics

Publication Date: 2024-01-01

Volume: 453

Issue: Unknown

Page Range: 601-613

Description:

Earlier research results suggest that certain optimization processes take place in the human nervous system during body movement including locomotion. These processes might employ a combination of cost functions that make adaptation possible to the changing conditions, such as terrain or to certain intentions such as maintaining locomotion speed. We focus on the exploration of the changes in human body kinematics and kinetics, related to well-defined cost functions, such as energy dissipation, energy conservation or energy accumulation. These cost functions are in analogy with deceleration, constant speed locomotion and acceleration. Hence, we collected measurement data of eight athletes with five different tasks: (1) slow, (2) convenient, (3) high speed running, (4) acceleration and (5) deceleration. Correlation tests showed that the effect of varying speed and acceleration can be distinguished. The variation in running speed can be effectively indicated by the knee angle, the relative horizontal position of the center of mass and the center of foot pressure (CoM-CoP distance), the loading rate, the peak tibial shock, the foot angle and the shank angle, while the variation in the acceleration can be indicated by the angle of the trunk, the CoM-CoP distance, the average ground reaction force angle and the horizontal force components in the joints.

Open Access: Yes

DOI: 10.1007/978-3-031-56492-5_44

Discrete time stability of augmented Lagrangian formalism based underactuated inverse dynamics control method

Ambrus Zelei R. Zana

Publication Name: JVC Journal of Vibration and Control

Publication Date: 2025-10-01

Volume: 31

Issue: 19-20

Page Range: 4445-4468

Description:

Stability problems of robotic systems arise sometimes suddenly, seemingly for no reason. The digital time sampling is often the main cause of these instabilities. Discrete models, which are capable of the prediction of stability, are available for low-degree-of-freedom template models of linear position and force control. However, for the inverse dynamics control of underactuated systems, the literature has a lack of generally applicable results related to the effect of time discretization. Several control approaches are available in the literature out of which a widely used one, the augmented Lagrangian formalism and its stability properties are analysed in this work. Theoretical stability properties are obtained for a generally usable, linear, underactuated, two-degree-of-freedom constrained template model. The actuator dynamics, the finite difference approximation of the feedback velocity and the filtering of the feedback data are considered in the model. These phenomena strongly affects the stability properties. The theoretically obtained stability maps are experimentally validated on an underactuated crane-like indoor robot. The position and orientation accuracy of the robot were assessed: the absolute position error was below 30 mm and the orientation error was below 3°.

Open Access: Yes

DOI: 10.1177/10775463241280339

Control of underactuated systems based on machine learning model: case studies

Ambrus Zelei

Publication Name: Multibody System Dynamics

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Besides traditional modelling approaches, machine learning surrogate models have become widespread. In addition to existing concepts, this work investigates the use of neural networks (NNs) to replace dynamic equations in multibody systems. While physics-informed neural networks (PINNs) dominate recent literature, their constraint enforcement via cost-function penalties poses tuning challenges. This paper proposes an alternative: training NNs on data with intentional constraint violations to implicitly learn stabilisation, avoiding PINN limitations. The proposed concept is applied to the inverse dynamics control of underactuated systems, where the task is defined by servo-constraints. Using Scikit-learn’s MLP Regressor, we demonstrate NN-based surrogate modeling in three levels: 1) forward dynamics of minimum-coordinate models, 2) constrained models, and 3) the inverse dynamics control of underactuated multibody systems via servo-constraints, which is a classical approach not yet combined with NNs. The neural network model is used to represent the inverse dynamics model, for which training data are generated through forward dynamic simulations. The study demonstrates that low-degree-of-freedom planar systems can be approximated by middle-scale neural network models of a few hundred perceptrons, requiring training times of minutes on a personal computer. The proposed control architecture can stabilise the servo-constraints and track trajectories, even for non-collocated underactuated systems where traditional methods might fail. The results highlight a simple, industry-friendly path for NN-based MBD control.

Open Access: Yes

DOI: 10.1007/s11044-025-10116-7

Data-driven lifetime estimation of solder joints with various geometries

Ambrus Zelei Antal Bakonyi Zoltan Safar

Publication Name: Pollack Periodica

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Virtual lifetime estimation of microelectronic devices has become essential, due to the tightening requirements and the trend of electronification. Thermal cycling load cause fatigue crack in solder joints and therefore functional failures. The application of the fatigue models viable in the literature is circumstantial for industrial scale problems. The exploitation of the already existing simulation data in data-driven models is a promising solution for speeding up the virtual lifetime estimation process. This paper benchmarks data-driven methods to predict the lifetime of solder joints with different geometric properties using a dataset originated from finite element simulation results. This case study shows that the nonlinear function fitting and the neural network are applicable.

Open Access: Yes

DOI: 10.1556/606.2025.01301

Digital Twin Approaches for Gear NVH Optimization: A Literature Review of Modeling, Data Integration, and Validation Gaps

Ambrus Zelei Krisztian Horvath Krisztián Horváth Krisztián Horváth

Publication Name: Machines

Publication Date: 2025-12-01

Volume: 13

Issue: 12

Page Range: Unknown

Description:

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.

Open Access: Yes

DOI: 10.3390/machines13121141

Predicting Gear Noise Levels in Electric Multiple Units Based on Microgeometry Modifications Using Clustering and Inverse Distance Weighting †

Ambrus Zelei Krisztian Horvath Krisztián Horváth Krisztián Horváth

Publication Name: Engineering Proceedings

Publication Date: 2025-01-01

Volume: 113

Issue: 1

Page Range: Unknown

Description:

Reducing noise in electric multiple-unit (EMU) gearboxes demands prediction tools that are both rapid and reliable. Gear sound pressure levels vary sharply with micrometre-scale changes such as tooth repair, inclination, or profile relief, yet traditional estimates depend on hours-long CAE simulations. We present a data-driven hybrid surrogate that combines k-means clustering and inverse distance weighting (CLS-IDW) within the ODYSSEE A-Eye platform to map geometry modifications directly to broadband noise. Trained on the open 200-case Romax dataset, the model returns predictions within milliseconds and reproduces unseen operating points, with R2 = 0.75 and a mean absolute error of 2.33 dB, matching solver repeatability. Sensitivity analysis identifies a −7° tooth inclination coupled with a 10 µm repair depth as the most effective combination, lowering noise by 3–5 dB. Eliminating costly CAE loops, the surrogate supports acoustics-aware optimisation at the concept stage, compressing development cycles and enhancing passenger comfort while maintaining transparency for regulatory review.

Open Access: Yes

DOI: 10.3390/engproc2025113034

Multibody Simulation of Helical Gear Noise and Vibration Behavior Using MSC ADAMS †

Ambrus Zelei Krisztian Horvath Krisztián Horváth Krisztián Horváth

Publication Name: Engineering Proceedings

Publication Date: 2025-01-01

Volume: 113

Issue: 1

Page Range: Unknown

Description:

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.

Open Access: Yes

DOI: 10.3390/engproc2025113036

Sensitivity Analysis of SAC 305 Solder Polycrystal Mechanical Parameters and Predicted Fatigue Lifetime with Different Grain Structures

Ambrus Zelei Antal Bakonyi Levente Bodnár

Publication Name: Applied Sciences Switzerland

Publication Date: 2026-01-01

Volume: 16

Issue: 2

Page Range: Unknown

Description:

The microstructural behaviours of solder joints during thermomechanical stresses are still not fully understood, and the thermomechanical reliability of solder joints remains a research area for scientists. In many cases, the solder material is modelled as a homogeneous material in Finite Element-based lifetime estimation calculations, while the microstructural effects are neglected. The development of virtual lifetime estimation methods is required; these methods should involve grain structure and therefore provide accurate results for a variety of test cases under thermomechanical loading. This paper presents a meso-scale analysis of lead-free SAC305 solder polycrystals using DAMASK modelling of the grain structure of the solder material and emulating mechanical loading while investigating the mechanical response of the polycrystal. Our finding is that the orientations and grain sizes of the solder polycrystal have significant effects on the mechanical parameters, and these microstructural parameters could not be neglected, because the impact of these also has a very relevant impact on the estimated lifetimes.

Open Access: Yes

DOI: 10.3390/app16020704

Sensitivity analysis of tooth microgeometric modifications on vibroacoustic behaviour in helical gears with harmonically distributed variations

Ambrus Zelei Krisztián Horváth

Publication Name: Journal of Physics Conference Series

Publication Date: 2026-01-01

Volume: 3190

Issue: 1

Page Range: Unknown

Description:

The virtual acoustic testing of gear drives has gained growing importance. Fundamentally, the transmission error (TE) is predicted, since it directly affects the vibration and noise characteristics. In this study, the effect of the harmonically distributed tooth microgeometric variations on the TE is investigated via elastic multibody simulations of a helical gear pair. The sensitivity analysis focused on the tip relief, the root relief and the barrelling. The model considered different degrees of linear-, quadratic- and cubic-harmonically distributed variations. The results showed that barrelling with quadratic harmonic micro-geometry had the most significant effect on TE. In addition, if harmonic distributions accidentally coincide in the pairing of the gears, the TE is significantly amplified, leading to a pronounced excitation of the system dynamics.

Open Access: Yes

DOI: 10.1088/1742-6596/3190/1/012005