György Istenes

57191978596

Publications - 13

Analysis of the Effect of Mixed Eccentricity Fault on Controlled Induction Machines via Finite Element Method

György Istenes Krisztian Horvath

Publication Name: 2025 19th International Conference on Electrical Machines Drives and Power Systems Elma 2025 Proceedings

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The eccentricity in induction machines is a geometrical fault when the axis of rotation deviates from the ideal. As a result, the air gap between the stator and the rotor varies. Since the eccentricity is caused by a geometric misalignment, finite element method is used to model the fault in this paper and the phenomenon is detected by spectral analysis of the stator currents. In addition, the effect of eccentricity on the controlled drive is also investigated by numerical simulations.

Open Access: Yes

DOI: 10.1109/ELMA65795.2025.11083515

Area of Interest Tracking Techniques for Driving Scenarios Focusing on Visual Distraction Detection

P. Földesi György Istenes Viktor Nagy

Publication Name: Applied Sciences Switzerland

Publication Date: 2024-05-01

Volume: 14

Issue: 9

Page Range: Unknown

Description:

On-road driving studies are essential for comprehending real-world driver behavior. This study investigates the use of eye-tracking (ET) technology in research on driver behavior and attention during Controlled Driving Studies (CDS). One significant challenge in these studies is accurately detecting when drivers divert their attention from crucial driving tasks. To tackle this issue, we present an improved method for analyzing raw gaze data, using a new algorithm for identifying ID tags called Binarized Area of Interest Tracking (BAIT). This technique improves the detection of incidents where the driver’s eyes are off the road through binarizing frames under different conditions and iteratively recognizing markers. It represents a significant improvement over traditional methods. The study shows that BAIT performs better than other software in identifying a driver’s focus on the windscreen and dashboard with higher accuracy. This study highlights the potential of our method to enhance the analysis of driver attention in real-world conditions, paving the way for future developments for application in naturalistic driving studies.

Open Access: Yes

DOI: 10.3390/app14093838

Investigating the Effect of Gear Ratio in the Case of Joint Multi-Objective Optimization of Electric Motor and Gearbox

György Istenes József Polák

Publication Name: Energies

Publication Date: 2024-03-01

Volume: 17

Issue: 5

Page Range: Unknown

Description:

In this paper, a software framework is presented through an application that is able to jointly optimize an electric motor and a gearbox for the design of a drive system for electric vehicles. The framework employs a global optimization method and uses both analytical and finite element method (FEM) models to evaluate the objective functions. The optimization process is supported by a statistical surrogate model, which allows a large reduction of runtime. An earlier version of this framework was only suitable for electric motor optimization. In the application presented in a previous paper, the motor of a belt-driven electric drive system was optimized. In this paper, the optimization of the same drive system is shown, but now with a combined optimization of a gear drive and motor. The objective functions of optimization are minimizing the total loss energy and the weight of the drive system. The optimization results are compared with previous results to demonstrate the further potential of joint optimization.

Open Access: Yes

DOI: 10.3390/en17051203

FEM-Based Analysis of Induction Machine Broken Rotor Bar Detection Using Extended Kalman Filter

György Istenes Krisztian Horvath

Publication Name: 2024 23rd International Symposium on Electrical Apparatus and Technologies Siela 2024 Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper presents an extended Kalman filter-based (EKF-based) detection method of broken bars in induction machine (IM). The objective is to detect the change in rotor resistance of a cage induction machine in case of one or more broken bars. To analyze the proposed fault detector, simulations are carried out. In the applied simulation environment, finite element method (FEM) model is used to describe the electric behavior of IM. The broken bars are modelled in the FEM simulations.

Open Access: Yes

DOI: 10.1109/SIELA61056.2024.10637867

Nonlinear Identification of Lateral Dynamics of an Autonomous Car Vehicle †

Dániel Pup György Istenes Ferenc Szauter J. Bokor

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

In this paper, the nonlinear identification of the lateral dynamics of a road vehicle and the velocity dependence of the dynamics are presented. One of the most useful methods to define the mathematical model is system identification based on measured data. A test vehicle for autonomous driving was constrained to move in a straight line while the vehicle’s steering servo was artificially excited. The input of the system is therefore the sum of the artificial excitation and the control signal of the autonomous function, and the output is the lateral acceleration of the vehicle. The measurements are used to identify Wiener and Hammerstein models of the lateral dynamics at different speeds using nonlinear methods. The aim is to investigate the velocity dependence of the dynamics.

Open Access: Yes

DOI: 10.3390/engproc2024079053

Hammerstein Model Identification for Autonomous Vehicle Dynamics by Two-Stage Algorithm †

György Terdik Dániel Pup György Istenes J. Bokor

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

In this paper, the nonlinear identification (ID) of the lateral dynamics of a road vehicle is presented. The mathematical description of lateral dynamics is crucial for developing various self-driving functions. One method of describing dynamics is system identification from measured data. During the measurements, the steering servo of a test vehicle kept in straight-line motion by a self-driving function was artificially excited. A Hammerstein–Wiener model was successfully applied for the identification of these measurements. A nonlinear estimator was used during the fitting, which needed high computing power. For the Hammerstein–Wiener model, we used the two-stage algorithm (TSA) with a bilinear estimation method, which makes it possible to apply linear regression. We compared these methods during simulations and real data.

Open Access: Yes

DOI: 10.3390/engproc2024079054

Kriging-Assisted Multi-Objective Optimization Framework for Electric Motors Using Predetermined Driving Strategy

Peter Koros György Istenes Zoltan Pusztai Ferenc Friedler Zoltán Horváth

Publication Name: Energies

Publication Date: 2023-06-01

Volume: 16

Issue: 12

Page Range: Unknown

Description:

In this paper, a multi-objective optimization framework for electric motors and its validation is presented. This framework is suitable for the optimization of design variables of electric motors based on a predetermined driving strategy using MATLAB R2019b and Ansys Maxwell 2019 R3 software. The framework is capable of managing a wide range of objective functions due to its modular structure. The optimization can also be easily parallelized and enhanced with surrogate models to reduce the runtime. The framework is validated by manufacturing and measuring the optimized electric motor. The method’s applicability for solving electric motor design problems is demonstrated via the validation process. A test application is also presented, in which the operating points of a predetermined driving strategy provide the input for the optimization. The kriging surrogate model is used in the framework to reduce the runtime. The results of the optimization and the framework’s benefits and drawbacks are discussed through the provided examples, in addition to displaying the properly applicable design processes. The optimization framework provides a ready-to-use tool for optimizing electric motors based on the driving strategy for single- or multi-objective purposes. The applicability of the framework is demonstrated by optimizing the electric motor of a world recorder energy-efficient race vehicle. In this application, the optimization framework achieved a 2% improvement in energy consumption and a 9% increase in speed at a rated DC voltage, allowing the motor to operate at desired working points even with low battery voltage.

Open Access: Yes

DOI: 10.3390/en16124713

Control Algorithm Development of Electrical Drives by Using Finite Element Model in Connected MATLAB/Simulink and JMAG Framework

György Istenes Krisztian Horvath

Publication Name: 2023 18th Conference on Electrical Machines Drives and Power Systems Elma 2023 Proceedings

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This study presents a control algorithm development framework for electrical drives. In the proposed framework, MATLAB/Simulink and JMAG software are connected. Hence, the control algorithms under development can be investigated by simulations using a finite element process model. It provides a more accurate electromagnetic description than the lumped parameter type models. Therefore, the anisotropies of the machines can be considered during the development process of control algorithms. To demonstrate the application of the proposed framework, a simulation study on a controlled induction machine drive is presented.

Open Access: Yes

DOI: 10.1109/ELMA58392.2023.10202412

Multi-objective Optimization of Electric Motors with a Kriging Surrogate Model

György Istenes Zoltán Horváth

Publication Name: 2022 22nd International Symposium on Electrical Apparatus and Technologies Siela 2022 Proceedings

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Since the electric drive systems are already used in numerous cars and other vehicles as well, the widely varying fields of applications require custom motor design. The most efficient tool for different specified motor designs is the multi-objective optimization tool based on validated simulations. An electrical motor optimization system with a kriging surrogate model based on FEM simulations is developed. The application of this system is presented in this paper. The models and the simulations were created in ANSYS Maxwell and MATLAB. The optimization was performed with the multi-objective genetic optimization algorithm by MATLAB which can be controlled by a simple input-output MATLAB interface.

Open Access: Yes

DOI: 10.1109/SIELA54794.2022.9845694

Vibration analysis of a suspension system subject to high level of measurement noise

Gabor Rodonyi György Istenes Ferenc Szauter

Publication Name: 2017 4th International Conference on Control Decision and Information Technologies Codit 2017

Publication Date: 2017-11-08

Volume: 2017-January

Issue: Unknown

Page Range: 881-886

Description:

Using only vertical acceleration measurements for the sprung and unsprung masses of a suspension system of a commercial city bus, the goal of the paper is to develop an analysis method to find the vibration modes of the mechanical system from data measured during real life operation. The identified vibration modes can be used to (in)validate first principle physical models of the system, while the identified ARMA models can be used to develop uncertainty models. The challenge in the problem is that the measurements are subject to very high level of noise due to maneuvering of the vehicle, nonlinear effects of the suspension system, vibration of the engine and the gear system, and sensor noise. Nonparametric and parametric modeling methods are applied to evaluate the quality of the measurements and find the invariant properties of the suspension system. It is shown based on multiple experiments that independently of the actual road properties and operating conditions, eigen-frequencies of some vibration modes can be determined with relatively small uncertainty, while the corresponding damping factors have varying amount of uncertainty. Comparing the results with the modes of a full car vehicle model developed based on physical considerations, it can be concluded that an identification algorithm for obtaining the parameters of the physical model must be complemented with a suitable uncertainty modeling and classification.

Open Access: Yes

DOI: 10.1109/CoDIT.2017.8102707

AR and ARMA spectral analysis of suspension system of a commercial city bus

Gabor Rodonyi György Istenes Ferenc Szauter

Publication Name: Cinti 2016 17th IEEE International Symposium on Computational Intelligence and Informatics Proceedings

Publication Date: 2017-02-07

Volume: Unknown

Issue: Unknown

Page Range: 151-156

Description:

Concerning the increasing demand for intelligent and efficient urban vehicle systems with low cost maintainability and high passenger comfort, reliable methods are needed to model and to evaluate the imposed performances. The measurements, vibrations emerging on the wheels and the body, that has ben taken on a city bus are analyzed in the frequency domain. In this paper a parametric spectral analysis (AR/ARMA method) of the suspension system of a commercial city bus is presented. The goal of the analysis is to find the right structure for the systems. Parametric methods used in this paper justify and extend the results obtained by non-parametric ones and provide more accurate results for vibration analysis. One of the main conclusions of the investigations is that the quarter-car model structure based on first principles does not reflect the true frequency domain behavior of the system. Thus the identification of the physical model must be complemented with a suitable uncertainty modeling and classification.

Open Access: Yes

DOI: 10.1109/CINTI.2016.7846395

Spectral analysis of suspension system of a commercial city bus

Gabor Rodonyi György Istenes Ferenc Szauter

Publication Name: Sisy 2016 IEEE 14th International Symposium on Intelligent Systems and Informatics Proceedings

Publication Date: 2016-10-19

Volume: Unknown

Issue: Unknown

Page Range: 67-72

Description:

There is an ever increasing demand for intelligent and efficient urban vehicle systems that fulfill several requirements, e.g., low cost maintainability and high passenger comfort. Concerning these goals reliable methods are needed to model and to evaluate the imposed performances. In this paper a spectral analysis of the suspension system of a commercial city bus is presented. Based on experimental data taken on a city bus, the vibrations emerging on the wheels and the body are analyzed in the frequency domain. The goal of the analysis is to characterize the main eigenfrequencies of the suspension system and its damping in amplitude and also to evaluate both the road and the suspension system in terms of passenger comfort according to ISO standards.

Open Access: Yes

DOI: 10.1109/SISY.2016.7601473

Integrated urban air pollution dispersion modelling framework and application in air quality prediction of the city of győr

É V.P. Rácz L. Környei Balázs Szintai István Harmati György Istenes Bence Liszkai Péter Zsebők Zoltán Horváth

Publication Name: Harmo 2016 17th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes Proceedings

Publication Date: 2016-01-01

Volume: 2016-May

Issue: Unknown

Page Range: 410-414

Description:

Model accuracy versus model running time - urban air pollution dispersion modellers have to balance between them when selecting models to be implemented. CFD based models seem to be the best candidates for an accurate model that can be validated at urban scale at highest level on the price of a longer running time. In this paper we shall introduce 3DAirQC software framework which addresses a portable and validated CFD model for air quality prediction and control.

Open Access: Yes

DOI: DOI not available