Krisztian Horvath

57192820466

Publications - 23

Data-Driven Identification of Gearbox Housing Structures Using Acoustic Radiation Spectra

Krisztian Horvath

Publication Name: International Journal of Basic and Applied Sciences

Publication Date: 2025-08-01

Volume: 14

Issue: 4

Page Range: 619-623

Description:

The structural design of gearbox housing, such as ribbing and wall thickness, has a significant impact on its noise radiation characteristics, especially in electric vehicle applications where tonal noise is more perceptible. This study presents a novel methodology that uses machine learning and spectral analysis to distinguish between gearbox housing types based solely on their acoustic radiation data. Frequency-domain sound pressure spectra, simulated for multiple design variants, were interpolated and analyzed using Principal Component Analysis (PCA) and K-means clustering. The results reveal that construction types (e.g., fully ribbed, partially ribbed, or without ribs) exhibit distinct acoustic profiles. Furthermore, a Random Forest classifier achieved 88.9% accuracy in predicting structural configuration from the spectra alone. These findings demonstrate that structural design features can be inferred directly from acoustic data, offering a lightweight and geometry-free alternative to traditional NVH simulation workflows. The approach can be integrated as a lightweight plug-in in existing NVH workflows. It ingests acoustic spectra and returns a structural-stiffness label with uncertainty, supporting early-stage screening and late-phase regression checks.

Open Access: Yes

DOI: 10.14419/mnbhp030

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

Demagnetization Fault Detection and Fault-Tolerant Control for PMa-SynRM Drive Using EKF-Based Permanent Magnet Flux Linkage Estimator

Krisztian Horvath Zoltan Nemeth Tamás Horváth

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:

Demagnetization faults in permanent magnetassisted synchronous reluctance motors (PMa-SynRMs) can lead to deterioration in the control performance of the drives, if the implemented PM flux linkage parameter is different from the actual value. To increase the robustness against demagnetization faults, a novel fault-tolerant control method is developed for PMa-SynRM drives. In the proposed method, an extended Kalman filter is used for online estimation of the PM flux linkage, which is tuned adaptively in the control algorithm, including the maximum torque per ampere strategy. The effectiveness of the proposed demagnetization fault-tolerant control technique is demonstrated by numerical simulations.

Open Access: Yes

DOI: 10.1109/ELMA65795.2025.11083424

HF Pulse Signal Injection Based Method for Sensorless Control of PMSM with Cogging Torque Compensation

Karol Kyslan Grzegorz Tarchala Karol Wróbel Krisztian Horvath Viktor Petro

Publication Name: Proceedings 2025 IEEE 7th Global Power Energy and Communication Conference Gpecom 2025

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 257-262

Description:

High-frequency (HF) signal injection methods are one of the key techniques for accurately estimating the rotor position of permanent magnet synchronous machines (PMSMs). The rotor position is determined by superimposing HF signals onto the fundamental control signals, producing a combined signal that serves as a reference for the PWM modulator. The rotor position is then extracted from the current response caused by the injected signal. This paper introduces a modification to the HF pulse signal injection method for sensorless control. The proposed approach improves control dynamics by reducing the signal injection period from two control periods to just one, and by adding the cogging torque compensation, thereby minimizing current and speed ripple. Experimental results obtained with a 2.5 kW PMSM and RT-LAB software obtained for the 1% of nominal speed validate the effectiveness of the proposed method.

Open Access: Yes

DOI: 10.1109/GPECOM65896.2025.11061829

Tensor Product Alternatives for Nonlinear Field-Oriented Control of Induction Machines

Miklós Kuczmann Krisztian Horvath

Publication Name: Electronics Switzerland

Publication Date: 2024-04-01

Volume: 13

Issue: 7

Page Range: Unknown

Description:

The paper presents a nonlinear field-oriented control technique based on the tensor product representation of the nonlinear induction machine model and the solvability of linear matrix inequalities. The nonlinear model has 32 quasi linear parameter-varying equivalent variants, and it is shown that only half of the models result in feasible controller. Two control goals are realized: torque control and speed control. The controller is a nonlinear state feedback controller completed by integral action. A new block diagram is investigated for speed control. The controller gains are designed by the solution of linear matrix inequalities to solve the Lyapunov inequality to obtain a stable and fast response and constraints on the control signal. The presented methods are verified and compared by simulations.

Open Access: Yes

DOI: 10.3390/electronics13071405

Online Inductance Identification Using Extended Kalman Filter for Adaptive Vector Control of Synchronous Reluctance Machine

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 study presents an adaptive vector control method for reducing the inductance sensitivity of synchronous reluctance machine drives. In the proposed control structure, the direct and quadrature inductances are identified online by using an extended Kalman filter. Therefore, only the stator resistance of the machine parameters needs to be pre-identified during the installation process. Since variations in inductances can be tracked by the estimator, the proposed adaptive vector control is able to outperform the conventional field-oriented control in cases of inductance uncertainties, as shown by the simulation results.

Open Access: Yes

DOI: 10.1109/SIELA61056.2024.10637878

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

Impact of Coordinate System Selection and Model Observability on Position Sensorless State Estimation of Nonsalient-Pole PMSM

Miklós Kuczmann Krisztian Horvath

Publication Name: 2024 IEEE 21st International Power Electronics and Motion Control Conference Pemc 2024

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Model observability is essential for the design of state estimators and observers, since the state vector can only be fully reconstructed from the measurements, if the model is observable. However, some research articles do not perform observability analysis and use unobservable models, while the presented results show adequate estimation performance. This paper deals with the impact of observability on the position sensorless state estimation of nonsalient-pole permanent magnet synchronous machine (PMSM). To show how the observability depends on the chosen coordinate system, observability studies are presented for two widely used nonlinear state-space models given in either the stator or the rotor reference frame. For the stationary reference frame model, a necessary and sufficient observability condition is defined, and it is shown that the model using rotor-oriented variables is unobservable. To point out the limitations of using the unobservable model, comparative simulations are carried out between extended Kalman filters using the models presented.

Open Access: Yes

DOI: 10.1109/PEMC61721.2024.10726413

Position sensorless extended and unscented Kalman filters with permanent magnet flux linkage and load torque estimation for surface-mounted PMSM

Krisztian Horvath

Publication Name: Automatika

Publication Date: 2024-01-01

Volume: 65

Issue: 3

Page Range: 1201-1212

Description:

In this paper, novel position sensorless state estimators with improved robustness to permanent magnet (PM) flux linkage variations in permanent magnet synchronous machines (PMSMs) are presented. Unlike state estimators using conventional infinite inertia or electromechanical models, the estimators presented here can also estimate the PM flux linkage, so they are not sensitive to its uncertainty. For each models used for state estimation, a detailed observability study is presented. Due to the nonlinear models, extended and unscented Kalman filter algorithms are used for the implementation. To compare the sensitivity of conventional and proposed state estimators to uncertainty in electrical parameters, numerical simulations are carried out. In addition, the computational burden of the estimators is compared by real-time execution.

Open Access: Yes

DOI: 10.1080/00051144.2024.2354643

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

Comparison of Extended and Unscented Kalman Filters with and without Using Mechanical Model for Speed Sensorless Control of Induction Machines

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:

In this work, speed sensorless state estimators are compared for induction machine drives. The studied estimators are based on two widely used state-space models. The first one has five state variables and assumes slowly varying rotor speed. In contrast, the second model is augmented by the equation of motion and the load torque is defined as an additional state variable. Due to the nonlinearities, extended and unscented Kalman filters are applied in the case of both models. To compare the parameter sensitivities and the low speed operation of the four state estimators, simulations and experiments are carried out. In addition, the estimators are also tested in speed sensorless closed-loop control structure.

Open Access: Yes

DOI: 10.1109/ELMA58392.2023.10202302

Impact of Iron Loss on Performance of Speed Sensorless MRAS Estimator for Induction Machines

Krisztian Horvath Diána Sarolta Kiss

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:

In this work, the impact of iron loss on speed estimation performance of the conventional rotor flux error-based model reference adaptive system (MRAS) estimator is investigated in case of induction machines (IMs). In addition, two improved MRAS-type estimators are proposed to reduce the estimation error caused by iron loss. The first approach takes into account iron loss resistance by its nominal constant value. But in the second case, iron loss is frequency dependent. All three estimators are compared by simulations. The results show that the MRAS estimators with iron loss compensation can reduce the speed estimation error and the frequency dependent iron loss compensation method provides the highest accuracy.

Open Access: Yes

DOI: 10.1109/SIELA54794.2022.9845766

Statistical approach for designing generic 18650 battery model

Adrienn Dineva István Lakatos Krisztian Horvath Szabolcs Kocsis Szurke

Publication Name: 2021 17th Conference on Electrical Machines Drives and Power Systems Elma 2021 Proceedings

Publication Date: 2021-07-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Most battery models are designed by estimating its parameters of one or two different cells. During simulations, these models perform satisfactorily and produce results very close to reality. The problem occurs when measurements are conducted with cells from different manufacturers and large variations are observed during the dynamic loads. The purpose of this paper is to design a general model for 18650 designed batteries, which provides as little deviation as possible when using different cell types. To establish the general model, constant load, transient, and dynamic load tests on 8 different cells are performed. An Ordered Weighted Averaging operator is used to standardize the measurement results and determine the model parameters. Outliers are filtered out using the weight parameter. To create the battery model a two-time-constant circuit model is used in MATLAB Simulink. Worldwide Harmonized Light Vehicle Test Procedure (WLTP) tests are used to validate the results.

Open Access: Yes

DOI: 10.1109/ELMA52514.2021.9503034

Design of Feedback Linearization Controllers for Induction Motor Drives by using Stator Reference Frame Models

Miklós Kuczmann Krisztian Horvath

Publication Name: Proceedings 2021 IEEE 19th International Power Electronics and Motion Control Conference Pemc 2021

Publication Date: 2021-04-25

Volume: Unknown

Issue: Unknown

Page Range: 766-773

Description:

The paper presents feedback linearization based nonlinear controller design for induction machine torque and speed control. Two state-space representation have been studied, stator currents and rotor mechanical speed are measured to control the drive. The pole placement technique is applied to design controller and an integral action is appended to reach accurate steady-state behavior and improve robustness. The presented methods are verified and compared by simulations.

Open Access: Yes

DOI: 10.1109/PEMC48073.2021.9432503

Observability Conditions for Speed Sensorless Induction Motor Models with Neglected or Included Iron Loss Representation

Krisztian Horvath

Publication Name: International Conference on Electical Drives and Power Electronics

Publication Date: 2021-01-01

Volume: Unknown

Issue: Unknown

Page Range: 97-101

Description:

Iron loss is usually neglected in induction motor models used for speed sensorless control and observer design. Thus, the complexity of control and estimator algorithms are reduced. However, the application of a more accurate model can improve the performance, hence the inclusion of iron loss in the machine model is becoming more widespread. But the effect of iron loss modeling on observability has not been analyzed yet. In this paper, observability conditions are presented for nonlinear state-space models with included iron loss. Furthermore, the results are compared with the observability properties of the traditional models where iron loss is ignored.

Open Access: Yes

DOI: 10.1109/EDPE53134.2021.9604110

Model-based control algorithm development of induction machines by using a well-defined model architecture and rapid control prototyping

Krisztian Horvath Marton Kuslits Szilárd Lovas

Publication Name: Electrical Engineering

Publication Date: 2020-09-01

Volume: 102

Issue: 3

Page Range: 1103-1116

Description:

This paper presents a new control algorithm development approach for induction machines by using model-based design and a systematically built model architecture implemented in MATLAB/Simulink. The model architecture follows a three-layer structure, and it is developed according to the principle of functional decomposition and the needs of reusability and expandability. The first model layer consists of elementary model and algorithm components, the second contains a machine simulation model and a field-oriented control (FOC) algorithm, built upon the first layer’s components, and the third realises the executable models by connecting the models and algorithms defined in the second layer. Furthermore, rapid control prototyping (RCP) is discussed as an experimental validation method, and an experimental setup with RCP is also introduced. The application of the presented methods is demonstrated by simulations as well as by experiments, and by using a control algorithm based on FOC as an example.

Open Access: Yes

DOI: 10.1007/s00202-020-00935-6

Low speed operation of sensorless estimators for induction machines using extended, unscented and cubature kalman filter techniques

Krisztian Horvath Denes Fodor

Publication Name: International Conference on Electical Drives and Power Electronics

Publication Date: 2019-09-01

Volume: 2019-September

Issue: Unknown

Page Range: 279-285

Description:

In this study, three feasible speed sensorless estimators of induction machines are presented by using extended, unscented and cubature Kalman filter algorithms. The estimators are based on an augmented non-linear state-space model of these machines, which describes the dynamics in stationary reference frame with six state variables. As an important part of the estimator design, an observability study is provided for the nonlinear model and an observability condition is formulated as well. The estimators are compared experimentally around zero stator frequency with respect to the speed estimation performance. However, the estimators are investigated only in open-loop and without external load disturbance.

Open Access: Yes

DOI: 10.1109/EDPE.2019.8883936

Parameter Sensitivity Analysis Method for Speed Sensorless Induction Machine Drives Based on Unscented Kalman Filter

Krisztian Horvath Marton Kuslits

Publication Name: Proceedings 2018 IEEE 18th International Conference on Power Electronics and Motion Control Pemc 2018

Publication Date: 2018-11-03

Volume: Unknown

Issue: Unknown

Page Range: 744-749

Description:

This paper presents a new method for determining the steady-state machine parameter sensitivities of induction machine speed sensorless control algorithms, which are utilizing unscented Kalman filter (UKF) and direct rotor field oriented control (DRFOC). Sensitivity influence of the UKF is investigated by alternative noise parameters and pointed out that selection of noise parameters may influence the flux and torque sensitivities of the entire system with respect to stator resistance variations. In order to obtain a better picture, the sensitivities are calculated for various operating points resulting in sensitivity maps. For this, a computationally efficient calculation method is applied by using the steady-state system equations.

Open Access: Yes

DOI: 10.1109/EPEPEMC.2018.8521843

Cubature kalman filter-based speed sensorless control of induction machines

Krisztian Horvath

Publication Name: 2018 20th International Symposium on Electrical Apparatus and Technologies Siela 2018 Proceedings

Publication Date: 2018-08-24

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this paper, a new speed sensorless control algorithm is introduced for induction machine (IM) drives, which utilizes the cubature Kalman filter (CKF) as state estimator. The CKF is a relative new approach to nonlinear state estimation, which uses a spherical-radial cubature rule in order to compute numerically the multivariate moment integrals. Using an augmented state space model of the IMs, CKF provides load torque estimation and sufficient control performance under difficult operating conditions. The proposed control algorithm is validated by MATLAB simulation in this work.

Open Access: Yes

DOI: 10.1109/SIELA.2018.8447157

Optimization-based parameter tuning of unscented Kalman filter for speed sensorless state estimation of induction machines

Krisztian Horvath Marton Kuslits

Publication Name: Proceedings 2017 5th International Symposium on Electrical and Electronics Engineering Iseee 2017

Publication Date: 2017-12-07

Volume: 2017-December

Issue: Unknown

Page Range: 1-7

Description:

State estimation of induction machines may be a difficult problem, due to the non-linear behavior of theirs. For non-linear state estimation, the unscented Kalman filter (UKF) is a well-known extension of the linear Kalman filter. Operation of the UKF algorithm strongly depends on the process and measurement noise covariance parameters of the estimator. Determination of these parameters is not straightforward and can be difficult, especially if the number of state variables and hence the system complexity is relatively high. In this paper, the UKF algorithm is applied for speed sensorless state estimation of induction machines in such a way that seven state variables are estimated from the measured stator currents and from the known excitation voltages. In order to tune the noise parameters of the UKF, a new, optimization-based method is presented. This tuning method provides adequate behavior for the observer beside difficult operating conditions as it has been shown by simulation experiment.

Open Access: Yes

DOI: 10.1109/ISEEE.2017.8170649

Design of load torque and mechanical speed estimator of PMSM with unscented Kalman filter-An engineering guide

Karol Kyslan Frantisek Durovsky Viliam Fedak Viktor Slapak Krisztian Horvath

Publication Name: International Conference on Electical Drives and Power Electronics

Publication Date: 2017-11-27

Volume: 2017-October

Issue: Unknown

Page Range: 297-302

Description:

This paper presents the design of Unscented Kalman Filter (UKF) for estimation of state space variables of permanent magnet synchronous machine (PMSM). The UKF is shown together with the field oriented speed control. At first, the position and the speed of PMSM are measured, and UKF is used only for a load torque estimation. It is indicated how differences in sampling time of the speed and the current loop affects overall estimation performance. Subsequently, speed sensorless performance of the UKF with the same parameters is shown for comparison. Designed filter is verified only by Matlab simulation.

Open Access: Yes

DOI: 10.1109/EDPE.2017.8123249

Speed sensorless field oriented control of induction machines using unscented kalman filter

Krisztian Horvath Marton Kuslits

Publication Name: Proceedings 2017 International Conference on Optimization of Electrical and Electronic Equipment Optim 2017 and 2017 Intl Aegean Conference on Electrical Machines and Power Electronics Acemp 2017

Publication Date: 2017-07-11

Volume: Unknown

Issue: Unknown

Page Range: 523-528

Description:

In this paper, an observer-based speed sensorless field oriented control (FOC) algorithm is presented for induction machines. The state observer is based on a new, detailed observer model which describes the machine with seven state variables, i.e. with seven equations. Since these equations are strongly non-linear, the applied observer algorithm is the unscented Kalman filter (UKF). Using the advantages of the detailed non-linear model and the UKF algorithm, the state variables can be estimated adequately, including the rotor flux position. Using these variables a speed sensorless FOC structure has been developed.

Open Access: Yes

DOI: 10.1109/OPTIM.2017.7975021

Model-Based development of induction motor control algorithms with modular architecture

Krisztian Horvath Marton Kuslits

Publication Name: Proceedings 2016 IEEE International Power Electronics and Motion Control Conference Pemc 2016

Publication Date: 2016-11-21

Volume: Unknown

Issue: Unknown

Page Range: 133-138

Description:

Development of control algorithms for electrical machines may be a difficult procedure if functional safety, software quality, reusability and expandability come into scope. These properties might be required in both of research and industrial development projects. State of the art methods and tools like model-based design (MBD) and automated code generation may help to meet these requirements. In this paper, MBD methods and a modular, reusable model architecture are presented for implementation of field oriented control (FOC)-based controller software for induction motors.

Open Access: Yes

DOI: 10.1109/EPEPEMC.2016.7751987