Gergő Sütheö

58027721700

Publications - 8

Accident Risk Analysis of Road Accidents Involving Personal Injury

István Lakatos Gergő Sütheö Péter Brúnó

Publication Name: Periodica Polytechnica Transportation Engineering

Publication Date: 2025-01-01

Volume: 53

Issue: 3

Page Range: 301-307

Description:

In both the European Union Member States and Hungary, a large number of people are killed in road traffic accidents. Reducing road collisions, personal injuries, and fatalities is a priority. To get an accurate picture of the situation, it is necessary to know the accident statistics of the European Union and the main EU directives that define a Safe Transport System. We then review the road safety situation in Hungary, using data from 2017 to 2020. In preparing the statistical overview, particular attention will be paid to the spatial distribution of severity, over time and by county, the distribution of accident participants by type of transport, the characteristics of the persons involved in the accident, the causes of the accidents and the distribution by type of accident. The analysis includes an explanation of the variables related to the vehicles involved in the accident and the causes of accidents related to human factors.

Open Access: Yes

DOI: 10.3311/PPtr.38004

Emission analysis of liquefied natural gas and diesel heavy-duty trucks using on-board monitoring method

Gergő Sütheö Marton Jagicza Balázs Baráth

Publication Name: Journal of Ecological Engineering

Publication Date: 2025-01-01

Volume: 26

Issue: 2

Page Range: 258-271

Description:

Environmental protection and the reduction of greenhouse gas (GHG) emissions are becoming top priorities in the mobility sector especially in heavy-duty truck (HDT) sector. In recent years, numerous regulations, targets, and initiatives have been introduced, all of which strongly promote the reduction of carbon-dioxide (CO2) emissions, the adoption of eco-friendly alternatives, and the use of renewable energy sources. The study compares CO2 emissions and fuel consumption between conventional diesel and liquefied natural gas (LNG) heavy-duty vehicles (HDVs) from the same original equipment manufacturer (OEM). The research was conducted on multiple levels, with a primary focus on control based on test track measurements. This was preceded by a simulation phase and followed by public road measurement-based validation process. In this study, we used the onboard monitoring (OBM) emission analysis method, a cost-effective and accurate process where data was recorded from the fleet management system (FMS) using controller area network (CAN) messages. The results are presented in several stages from simulation to data validation. Our research represents a unique study in the field of HDVs, as the measurements were conducted on a test track, supported by simulations and public road tests. The results of the project clearly demonstrate that gas technology can contribute to reducing GHG emissions in HDVs, and LNG provides a reliable alternative for long-distance transportation.

Open Access: Yes

DOI: 10.12911/22998993/195574

Investigation of the impact of a solar panel system installed on an heavy-duty truck trailer on fuel consumption at the ZalaZONE test track

András Háry Gergő Sütheö Leticia Pekk Richárd Peszleg

Publication Name: Advances in Science and Technology Research Journal

Publication Date: 2025-01-01

Volume: 19

Issue: 4

Page Range: 304-310

Description:

This study evaluates the impact of a solar panel system installed on a heavy-duty truck (HDV) trailer on fuel consumption, tested at the ZalaZONE track. Two vehicles were assessed – diesel-powered and an liquefied natural gas (LNG) powered truck, with the latter equipped with solar panels. Over five days, the solar system powered cabin electronics, reducing idle time and fuel use. While fuel and carbon dioxide (CO₂) savings were observed, performance was limited by battery charge and sunlight exposure. The results show potential for up to 10% fuel savings, demonstrating the system’s feasibility for reducing emissions in long-haul transport, though further optimization is needed.

Open Access: Yes

DOI: 10.12913/22998624/200029

Comparison of Carbon-Dioxide Emissions of Diesel and LNG Heavy-Duty Trucks in Test Track Environment

András Háry Gergő Sütheö

Publication Name: Clean Technologies

Publication Date: 2024-12-01

Volume: 6

Issue: 4

Page Range: 1465-1479

Description:

Environmental protection and greenhouse gas (GHG) emissions are getting increasingly high priority in the area of mobility. Several regulations, goals and projects have been published in recent years that clearly encourage the reduction of carbon dioxide (CO2) emission, the adoption of green alternatives and the use of renewable energy sources. The study compares CO2 emissions between conventional diesel and liquefied natural gas (LNG) heavy-duty vehicles (HDVs), and furthermore investigates the main influencing factors of GHG emissions. This study was carried out in a test–track environment, which supported the perfect reproducibility of the tests with minimum external influencing factors, allowing different types of measurements. At the results level, our primary objective was to collect and evaluate consumption and emission values using statistical methods, in terms of correlations, relationships and impact assessment. In this research, we recorded CO2 and pollutant emission values indirectly via the fleet management system (FMS) using controller area network (CAN) messages. Correlation, regression and statistical analyses were used to investigate the factors influencing fuel consumption and emissions. Our scientific work is a unique study in the field of HDVs, as the measurements were performed on the test track level, which provide accuracy for emission differences. The results of the project clearly show that gas technology can contribute to reducing GHG emissions of HDVs, and LNG provides a reliable alternative way forward for long-distance transportation, especially in areas of Europe where filling stations are already available.

Open Access: Yes

DOI: 10.3390/cleantechnol6040070

Development of a Battery Diagnostic Method Based on CAN Data: Examining the Accuracy of Data Received via a Communication Network

Gergő Sütheö Leticia Pekk Balázs Baráth

Publication Name: Energies

Publication Date: 2024-11-01

Volume: 17

Issue: 22

Page Range: Unknown

Description:

In order to reduce the emissions caused by internal combustion engine vehicles, the industry is introducing more and more electric or hybrid vehicles to the market nowadays. The battery cells and modules of these vehicles require a lot of care, as improper or improperly maintained battery units can cause serious problems inside vehicles and can be extremely dangerous. The safest solution is to keep this unit of a vehicle under constant supervision so that it can be repaired immediately in case of an issue. Since all necessary data can be extracted from a vehicle’s communication network(s) through standard communication protocols, it is advisable to use them for continuous monitoring and diagnostics of units, while also considering cost-effectiveness and simplicity. The data received from here can also be used for measurement of electric powertrains and other parameters. However, since these data go through many conversions and computers (ECUs) before reaching us, their accuracy is questionable. In this study, we present our own custom battery diagnostic tool based on data extracted from a communication network. With the help of commercially available diagnostic tools, we also compare several measurements of the extent of the error limits of the data arriving at the communication network, how far they differ from the real values, and with the help of these, we analyze the accuracy of the device we have made. We present the commonly used Controller Area Network (CAN) communication protocol for passenger vehicles and briefly describe the construction of the high-voltage battery unit of the test vehicle.

Open Access: Yes

DOI: 10.3390/en17225808

Self-Diagnostic Opportunities for Battery Systems in Electric and Hybrid Vehicles

István Lakatos Szabolcs Kocsis Szurke Péter Ori Gergő Sütheö

Publication Name: Machines

Publication Date: 2024-05-01

Volume: 12

Issue: 5

Page Range: Unknown

Description:

The number of battery systems is also growing significantly along with the rise in electric and hybrid car sales. Different vehicles use different types and numbers of batteries. Furthermore, the layout and operation of the control and protection electronics units may also differ. The research aims to develop an approach that can autonomously detect and localize the weakest cells. The method was validated by testing the battery systems of three different VW e-Golf electric vehicles. A wide-range discharge test was performed to examine the condition assessment and select the appropriate state of charge (SoC) for all three vehicles. On the one hand, the analysis investigated the cell voltage deviations from the average; the tests cover deviations of 0 mV, 12 mV, 60 mV, 120 mV, and 240 mV. On the other hand, the mean value calculation was used to filter out possible erroneous values. Another important aspect was examining the relationship between the state of charges (SoC) and the deviations. Therefore, the 10% step changes were tested to see which SoC level exhibited more significant voltage deviations. Based on the results, it was observed that there are differences between the cases, and the critical range is not necessarily at the lowest SoC level. Furthermore, the load rate (current) and time of its occurrence play an important role in the search for a faulty cell. An additional advantage of this approach is that the process currently being tested on the VW e-Golf can be relatively simply transferred to other types of vehicles. It can also be a very useful addition for autonomous vehicles, as it can self-test the cells in the system at low power consumption.

Open Access: Yes

DOI: 10.3390/machines12050324

Examination of the Load’s Effect on Fuel Consumption and CO2 Emissions, in the Case of a Diesel and LNG Powered Tractor †

Gergő Sütheö Marton Jagicza Gabor Laszlo Toth Balázs Baráth

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

This study compares the environmental impacts of diesel and LNG-powered tractors under varying loads, by utilizing a cost-effective measurement system on the ZalaZONE Proving Ground. The same test cycles and scenarios were conducted with both trucks simultaneously on the closed test track modules and the research highlights LNG’s advantages in reducing CO2 emissions, particularly under lower load conditions. This innovative approach, based on the fuel consumption rather than expensive exhaust gas analyzers, underscores LNG’s potential in meeting EU emission targets. The results support LNG as a competitive and sustainable alternative to diesel, promoting greener freight transport solutions for the future.

Open Access: Yes

DOI: 10.3390/engproc2024079017

Cell Fault Identification and Localization Procedure for Lithium-Ion Battery System of Electric Vehicles Based on Real Measurement Data

Szabolcs Fischer István Lakatos Szabolcs Kocsis Szurke Antal Apagyi Gergő Sütheö

Publication Name: Algorithms

Publication Date: 2022-12-01

Volume: 15

Issue: 12

Page Range: Unknown

Description:

Vehicle safety risk can be decreased by diagnosing the lithium-ion battery system of electric road vehicles. Real-time cell diagnostics can avoid unexpected occurrences. However, lithium-ion batteries in electric vehicles can significantly differ in design, capacity, and chemical composition. In addition, the battery monitoring systems of the various vehicles are also diverse, so communication across the board is not available or can only be achieved with significant difficulty. Hence, unique type-dependent data queries and filtering are necessary in most cases. In this paper, a Volkswagen e-Golf electric vehicle is investigated; communication with the vehicle was implemented via an onboard diagnostic port (so-called OBD), and the data stream was recorded. The goal of the research is principally to filter out, identify, and localize defective/weak battery cells. Numerous test cycles (constant and dynamic measurements) were carried out to identify cell abnormalities (so-called deviations). A query and data filtering process was designed to detect defective battery cells. The fault detection procedure is based on several cell voltage interruptions at various loading levels. The methodology demonstrated in this article uses a fault diagnosis technique based on voltage abnormalities. In addition, it employs a hybrid algorithm that executes calculations on measurement and recorded data. In the evaluation, a status line comprising three different categories was obtained by parametrizing and prioritizing (weighting) the individual measured values. It allows the cells to be divided into the categories green (adequate region), yellow (to be monitored), and red (possible error). In addition, several querying strategies were developed accordingly to clarify and validate the measurement results. The several strategies were examined individually and analyzed for their strengths and weaknesses. Based on the results, a data collection, processing, and evaluation strategy for an electric vehicle battery system have been developed. The advantage of the developed algorithm is that the method can be adapted to any electric or hybrid vehicle battery.

Open Access: Yes

DOI: 10.3390/a15120467