Peter Koros

57188825115

Publications - 21

Examination of the Resistance Components of an Energy-Efficient Electric Vehicle

Peter Koros Zoltan Pusztai Ferenc Szauter

Publication Name: Journal of Physics Conference Series

Publication Date: 2024-01-01

Volume: 2848

Issue: 1

Page Range: Unknown

Description:

The paper presents a comprehensive examination of measurement-based modelling regarding resistance forces. This work offers a detailed explanation of the experimental techniques employed to measure the resistance forces experienced by a lightweight vehicle. The modelling approach is particularly beneficial for characterizing vehicle with low resistance values. Our investigation encompasses key vehicle motion states, including cornering and straight-line motion, making it greatly useful for optimization purposes. The measurements were conducted in a proving ground and laboratory environment. The road load coefficients can be breakdown into components from total resistance force measurement. Based on breakdown, future vehicle development goals can be addressed with a focus on reducing resistance forces.

Open Access: Yes

DOI: 10.1088/1742-6596/2848/1/012011

Inverse Perspective Mapping Correction for Aiding Camera-Based Autonomous Driving Tasks †

Peter Koros Miklos Unger Norbert Marko

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

Inverse perspective mapping (IPM) is a crucial technique in camera-based autonomous driving, transforming the perspective view captured by the camera into a bird’s-eye view. This can be beneficial for accurate environmental perception, path planning, obstacle detection, and navigation. IPM faces challenges such as distortion and inaccuracies due to varying road inclinations and intrinsic camera properties. Herein, we revealed inaccuracies inherent in our current IPM approach so proper correction techniques can be applied later. We aimed to explore correction possibilities to enhance the accuracy of IPM and examine other methods that could be used as a benchmark or even a replacement, such as stereo vision and deep learning-based monocular depth estimation methods. With this work, we aimed to provide an analysis and direction for working with IPM.

Open Access: Yes

DOI: 10.3390/engproc2024079067

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

Implementation of Optimized Regenerative Braking in Energy Efficient Driving Strategies

Peter Koros Zoltan Pusztai Ferenc Szauter Ferenc Friedler

Publication Name: Energies

Publication Date: 2023-03-01

Volume: 16

Issue: 6

Page Range: Unknown

Description:

In this paper, determination of optimized regenerative braking-torque function and application in energy efficient driving strategies is presented. The study investigates a lightweight electric vehicle developed for the Shell Eco-Marathon. The measurement-based simulation model was implemented in the MATLAB/Simulink environment and used to establish the optimization. The optimization of braking-torque function was performed to maximize the recuperated energy. The determined braking-torque function was applied in a driving strategy optimization framework. The extended driving strategy optimization model is suitable for energy consumption minimization in a designated track. The driving strategy optimization was created for the TT Circuit Assen, where the 2022 Shell Eco-Marathon competition was hosted. The extended optimization resulted in a 2.97% improvement in energy consumption when compared to the result previously achieved, which shows the feasibility of the proposed methodology and optimization model.

Open Access: Yes

DOI: 10.3390/en16062682

Vehicle Model-Based Driving Strategy Optimization for Lightweight Vehicle

Peter Koros Zoltan Pusztai Ferenc Szauter Ferenc Friedler

Publication Name: Energies

Publication Date: 2022-05-01

Volume: 15

Issue: 10

Page Range: Unknown

Description:

In this paper, driving strategy optimization for a track is proposed for an energy efficient battery electric vehicle dedicated to the Shell Eco-marathon. A measurement-based mathematical vehicle model was developed to simulate the behavior of the vehicle. The model contains complicated elements such as the vehicle’s cornering resistance and the efficiency field of the entire powertrain. The validation of the model was presented by using the collected telemetry data from the 2019 Shell Eco-marathon competition in London (UK). The evaluation of applicable powertrains was carried out before the driving strategy optimization. The optimal acceleration curve for each investigated power-train was defined. Using the proper powertrain is a crucial part of energy efficiency, as the drive has the most significant energy demand among all components. Two tracks with different characteristics were analyzed to show the efficiency of the proposed optimization method. The optimization results are compared to the reference method from the literature. The results of this study provide an applicable vehicle modelling methodology with efficient optimization framework, which demonstrates 5.5% improvement in energy consumption compared to the reference optimization theory.

Open Access: Yes

DOI: 10.3390/en15103631

Regenerative Braking Optimization of Lightweight Vehicle based on Vehicle Model

Peter Koros Zoltan Pusztai Ferenc Szauter Ferenc Friedler

Publication Name: Chemical Engineering Transactions

Publication Date: 2022-01-01

Volume: 94

Issue: Unknown

Page Range: 601-606

Description:

The usage of regenerative braking highly improves the overall energy efficiency of electric vehicles. In this paper, the model-based optimization of the torque profile is determined in the regenerative braking process of a lightweight electric vehicle. For the optimization, measurement-based vehicle model was used, where the extended powertrain model was set up, including the regenerative operation. The whole model was elaborated in MATLAB Simulink environment, where genetic algorithm (GA) was applied for the optimization. The resulted optimized braking curve was applied to control the experimental vehicle and field test were made to validate the optimization results. The results of the presented work can be directly used to further improve the drive cycle efficiency of the urban electric vehicles. The application of optimized driving strategies, including regenerative braking, could contribute to further energy and pollution reduction in urban transportation.

Open Access: Yes

DOI: 10.3303/CET2294100

Data-driven linear parameter-varying modelling of the steering dynamics of an autonomous car

Gabor Rodonyi R. Tóth Peter Koros Dániel Pup Ádám Kisari Zsombor Vigh J. Bokor

Publication Name: IFAC Papersonline

Publication Date: 2021-07-01

Volume: 54

Issue: 8

Page Range: 20-26

Description:

Developing automatic driving solutions and driver support systems requires accurate vehicle specific models to describe and predict the associated motion dynamics of the vehicle. Despite of the mature understanding of ideal vehicle dynamics, which are inherently nonlinear, modern cars are equipped with a wide array of digital and mechatronic components that are difficult to model. Furthermore, due to manufacturing, each car has its personal motion characteristics which change over time. Hence, it is important to develop data-driven modelling methods that are capable to capture from data all relevant aspects of vehicle dynamics in a model that is directly utilisable for control. In this paper, we show how Linear Parameter-Varying (LPV) modelling and system identification can be applied to reliably capture personalised model of the steering system of an autonomous car based on measured data. Compared to other nonlinear identification techniques, the obtained LPV model is directly utilisable for powerful controller synthesis methods of the LPV framework.

Open Access: Yes

DOI: 10.1016/j.ifacol.2021.08.575

Identification of the nonlinear steering dynamics of an autonomous vehicle

Gabor Rodonyi R. Tóth M. Schoukens Peter Koros Dániel Pup Ádám Kisari G. I. Beintema Zsombor Vigh Alexandros Soumelidis J. Bokor

Publication Name: IFAC Papersonline

Publication Date: 2021-07-01

Volume: 54

Issue: 7

Page Range: 708-713

Description:

Automated driving applications require accurate vehicle specific models to precisely predict and control the motion dynamics. However, modern vehicles have a wide array of digital and mechatronic components that are difficult to model, manufactures do not disclose all details required for modelling and even existing models of subcomponents require coefficient estimation to match the specific characteristics of each vehicle and their change over time. Hence, it is attractive to use data-driven modelling to capture the relevant vehicle dynamics and synthesise model-based control solutions. In this paper, we address identification of the steering system of an autonomous car based on measured data. We show that the underlying dynamics are highly nonlinear and challenging to be captured, necessitating the use of data-driven methods that fuse the approximation capabilities of learning and the efficiency of dynamic system identification. We demonstrate that such a neural network based subspace-encoder method can successfully capture the underlying dynamics while other methods fall short to provide reliable results.

Open Access: Yes

DOI: 10.1016/j.ifacol.2021.08.444

Vehicle Model for Driving Strategy Optimization of Energy Efficient Lightweight Vehicle

Peter Koros Zoltan Pusztai Ferenc Friedler

Publication Name: Chemical Engineering Transactions

Publication Date: 2021-01-01

Volume: 88

Issue: Unknown

Page Range: 385-390

Description:

The energy consumption and CO2 emission of urban vehicles are highly dependent on their operation. Vehicle models can be used for optimizing driving strategy for emission reduction. This paper proposes a novel vehicle model of a one-seat electric vehicle dedicated for Shell Eco-marathon (SEM), the most famous and largest race of energy efficient vehicles. The available vehicle dynamical formulas cannot be directly used to describe the characteristics of lightweight vehicles. In the current work, a novel grey-box vehicle model has been introduced, based on measurement scenarios. The whole model has been elaborated in MATLAB Simulink environment, where individual subassemblies were defined for driving resistance model, powertrain model, and the racetrack characteristics. The resistance force model manages the forces in straight line moving and also takes the effect of cornering into account. Based on test bench measurements the complete efficiency map of the drivetrain was created and implemented into the vehicle model. The presented vehicle model is suitable for driving strategy optimization. By optimizing this model, 7.1 % energy savings have been achieved compared to best human driven lap. Driving strategy optimization will be essential, especially for autonomous vehicles, expressing the importance of the presented results in the future.

Open Access: Yes

DOI: 10.3303/CET2188064

Self-Driving Vehicle Sensors from One-Seated Experimental to Road-legal Vehicle

Ernö Horváth Zoltan Szeli Peter Koros Gábor Szakállas Peter Gulyas Zoltan Pusztai

Publication Name: Ines 2020 IEEE 24th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2020-07-01

Volume: Unknown

Issue: Unknown

Page Range: 97-101

Description:

Our university is determined to research and educate self-driving and autonomous technology. These two field require different necessities and attitude. In his paper we would like to summarize the migration from a road-legal vehicle to a self-developed, one-seated vehicle. We will describe the challenges of the migration process and of course how to overcome these challenges. The current paper also proposes recommendations and use-cases regarding self-driving vehicle sensory system.

Open Access: Yes

DOI: 10.1109/INES49302.2020.9147181

Development of Point-cloud Processing Algorithm for Self-Driving Challenges

Ernö Horváth Peter Koros Miklos Unger

Publication Name: Ines 2020 IEEE 24th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2020-07-01

Volume: Unknown

Issue: Unknown

Page Range: 91-95

Description:

The paper proposes an own-developed point-cloud processing algorithm which was developed for the Autonomous Urban Concept competition organized by Shell. The approach does not intend to solve general-purpose object recognition and tracking, although the methodologies presented can be used as general solutions. Our approach will be presented in comprehensive manner, the challenges and solutions will be detailed. Also, the dysfunctional ideas will be listed, and alternative workarounds will be presented as recommendations too. As verification of the algorithm, both simulation and real-world measurements will be presented. For the sake of research and open source, we share datasets and necessary information publicly.

Open Access: Yes

DOI: 10.1109/INES49302.2020.9147201

Experimental verification of a control system for autonomous navigation

Gabor Rodonyi Peter Koros Dániel Pup Ádám Kisari Benedek Szucs Alexandros Soumelidis J. Bokor

Publication Name: IFAC Papersonline

Publication Date: 2020-01-01

Volume: 53

Issue: 2

Page Range: 14273-14278

Description:

A flexible architecture is developed with the purpose of supporting education and research on the field of autonomous vehicles. A pure electric vehicle is equipped with on-board computational units, sensors and actuator interfaces. This paper presents the current status of the control system and its validation by means of navigation experiments. With the cascade control architecture, problems of actuator dead-zone, sensor offset errors, path tracking and redesign for obstacle avoidance are addressed.

Open Access: Yes

DOI: 10.1016/j.ifacol.2020.12.1171

Enhancement of pure-pursuit path-tracking algorithm with multi-goal selection

Csaba Hajdu Ernö Horváth Peter Koros

Publication Name: Gpmc 2019 1st IEEE International Conference on Gridding and Polytope Based Modeling and Control Proceedings

Publication Date: 2019-11-01

Volume: Unknown

Issue: Unknown

Page Range: 13-18

Description:

In this paper, we present an enhancement to the popular pure-pursuit algorithm, widely used in robotics and automotive applications. The original algorithm is simple and straightforward as it depends only on the very basic attributes of the kinematic model of the target mechanical system. The algorithm is usually tuned by choosing a look-ahead distance of points from the reference trajectory. On the other hand, pure-pursuit suffers from considerable tuning weaknesses highly attributed to improper selection of look-ahead distance, resulting in poor tracking performance. Our method proposes the dynamic change of lookahead distance based on selecting multiple-goal points, thus aiming a curvature fitting more the reference trajectory. Our work was motivated by an ongoing robotics and autonomous vehicle research project at our university.

Open Access: Yes

DOI: 10.1109/GPMC48183.2019.9106958

Novel Pure-Pursuit Trajectory Following Approaches and their Practical Applications

Csaba Hajdu Ernö Horváth Peter Koros

Publication Name: 10th IEEE International Conference on Cognitive Infocommunications Coginfocom 2019 Proceedings

Publication Date: 2019-10-01

Volume: Unknown

Issue: Unknown

Page Range: 597-602

Description:

Pure-pursuit algorithm is a popular trajectory tracking algorithm, widely used in mobile robotics and vehicular control for numerous reasons. The operation is simple and straightforward as it depends only on the kinematic model of the target mechanical system. The algorithm can be tuned by choosing look-Ahead distance of points of the reference trajectory. On the other hand, pure-pursuit suffers from weaknesses highly attributed to improper selection of look-Ahead distance, resulting in poor tracking performance. Recent developments focused on overcoming this drawback by dynamical change of this parameter. In this paper, we propose three enhancements to the original pure-pursuit algorithm, aiming to handle dynamic selection of look-Ahead distance by selecting multiple goals, modifying look-Ahead distance according to the curvatures and adjusting lateral deviation. Our work was motivated by an ongoing autonomous vehicle research at our university.

Open Access: Yes

DOI: 10.1109/CogInfoCom47531.2019.9089927

Research of required vehicle system parameters and sensor systems for autonomous vehicle control

András Mihály Peter Koros Dániel Pup Huba Somogyi Alexandros Soumelidis

Publication Name: Saci 2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2018-08-20

Volume: Unknown

Issue: Unknown

Page Range: 27-32

Description:

Our long-term goal is to implement autonomous vehicle control functions on a standard vehicle. At first we started with the investigation of the steering, which is a crucial area of the control of autonomous vehicles. As a part of the program, vehicle dynamical measurements were carried out on a Nissan Leaf electric vehicle equipped with a sensor system, furthermore we design a high-level trajectory-tracking controller.

Open Access: Yes

DOI: 10.1109/SACI.2018.8441008

Structure Selection and LPV Model Identification of a Car Steering Dynamics⁎

Gabor Rodonyi Zoltán Szabó Peter Koros Dániel Pup Alexandros Soumelidis J. Bokor

Publication Name: Unknown

Publication Date: 2018-01-01

Volume: 51

Issue: 15

Page Range: 1086-1091

Description:

A Linear Parameter-Varying (LPV), discrete-time black box model of an electric power assisted steering system of a passenger car is identified from open-loop step response measurement data. The goal is to provide a nominal model for control design and analysis that is able to describe the principal characteristics of the system in the whole region of steering angle and speed range of 3 to 30 km/h. Examining a set of experimental data by using classical linear time-invariant black box modeling and validation techniques, the structure of the LPV model is determined. The parameters of the model are identified based on minimizing a quadratic error criterion by nonlinear optimization algorithms.

Open Access: Yes

DOI: 10.1016/j.ifacol.2018.09.049

Two operating states-based low energy consumption vehicle control

István Lakatos Ernö Horváth Peter Koros Ferenc Szauter

Publication Name: Proceedings of the ASME Design Engineering Technical Conference

Publication Date: 2017-01-01

Volume: 9

Issue: Unknown

Page Range: Unknown

Description:

The current paper presents a realization of a complex vehicle control task. The goal was to consume the lowest possible energy in a less than 100 kg, wheel hub motor-driven vehicle. The realization is based on two distinguishable operating states which states characterizes well the driving cycle of the vehicle. The main contribution of the proposed method is that it reliably estimates the external loads which interacts the vehicle, the controller can adapt to this changes thus it can guarantee the minimal energy consumption. The vehicle described in the paper is a participant at the Shell Eco-marathon Europe competition in Urban Concept - Battery Electric category.

Open Access: Yes

DOI: 10.1115/DETC2017-67978

Systematic approach to software related tasks in electric fuel-efficiency vehicle development

Ernö Horváth Peter Koros

Publication Name: Ines 2015 IEEE 19th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2015-11-13

Volume: Unknown

Issue: Unknown

Page Range: 375-378

Description:

Nowadays software related tasks in experimental vehicle development are getting more and more attention. These tasks not only include the final product related software solutions such as the motor and the vehicle control algorithm or the telemetry system but even in the development process, applications are needed - for example on the motor test bench. The paper presents our ideas and solutions to software related tasks in vehicles for the whole development and validation process.

Open Access: Yes

DOI: 10.1109/INES.2015.7329737

Development of individual information technology systems of experimental vehicles

Peter Dely István Lakatos Ernö Horváth Peter Koros

Publication Name: Saci 2015 10th Jubilee IEEE International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2015-08-17

Volume: Unknown

Issue: Unknown

Page Range: 489-493

Description:

Two experimental vehicles were developed during the last two years in the Research Center of Vehicle Industry. The vehicles mentioned above are electrically driven and equipped with own developed computational modules. During development of the computational modules it was an important issue for us to create easily extendable systems which are easy-To-use. Different applications are realized in the two vehicles, consequently, different requirements were set up concerning our applications.

Open Access: Yes

DOI: 10.1109/SACI.2015.7208253

Operation and applicability issues of powertrain models in electric vehicle development

István Lakatos Peter Koros Viktor Nagy

Publication Name: Mesa 2014 10th IEEE ASME International Conference on Mechatronic and Embedded Systems and Applications Conference Proceedings

Publication Date: 2014-10-24

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The paper deals with researches started several years ago at the Department of Road and Rail Vehicles and Research Center of Vehicle Industry, Széchenyi István University. Simulation of electric driven vehicles and utilization of results are in focus.

Open Access: Yes

DOI: 10.1109/MESA.2014.6935610

A control strategy to minimize magnet losses in vehicle PMSM by field-weakening operation

Istvan Szenasy Zoltan Szeli Zoltan Varga Peter Koros

Publication Name: 2013 World Electric Vehicle Symposium and Exhibition Evs 2014

Publication Date: 2014-10-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

An applied control of PMSM is the flux weakening operation for extending the region over nominal speed on nominal voltage. This paper deals with these questions and its impacts. The proved method increases the torque angle and with this the d axis directed component of the stator current vector for reduce the main flux, but the loss developing in magnets became significant. These impacts and its reduction need several investigations. Our work indicates the possibilities and limits of flux-weakening for a given PMSM, and a usable control strategy.

Open Access: Yes

DOI: 10.1109/EVS.2013.6915035