Péter Ori

57507085700

Publications - 5

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

Brake Disc Deformation Detection Using Intuitive Feature Extraction and Machine Learning

István Lakatos Tamás Dózsa Erno Simonyi Péter Ori Mátyás Szabari Alexandros Soumelidis

Publication Name: Machines

Publication Date: 2024-04-01

Volume: 12

Issue: 4

Page Range: Unknown

Description:

In this work we propose proof-of-concept methods to detect malfunctions of the braking system in passenger vehicles. In particular, we investigate the problem of detecting deformations of the brake disc based on data recorded by acceleration sensors mounted on the suspension of the vehicle. Our core hypothesis is that these signals contain vibrations caused by brake disc deformation. Since faults of this kind are typically monitored by the driver of the vehicle, the development of automatic fault-detection systems becomes more important with the rise of autonomous driving. In addition, the new brake boosters separate the brake pedal from the hydraulic system which results in less significant effects on the brake pedal force. Our paper offers two important contributions. Firstly, we provide a detailed description of our novel measurement scheme, the type and placement of the used sensors, signal acquisition and data characteristics. Then, in the second part of our paper we detail mathematically justified signal representations and different algorithms to distinguish between deformed and normal brake discs. For the proper understanding of the phenomenon, different brake discs were used with measured runout values. Since, in addition to brake disc deformation, the vibrations recorded by our accelerometers are nonlinearly dependent on a number of factors (such as the velocity, suspension, tire pressure, etc.), data-driven models are considered. Through experiments, we show that the proposed methods can be used to recognize faults in the braking system caused by brake disc deformation.

Open Access: Yes

DOI: 10.3390/machines12040214

Vibration Diagnostic Methods of Automatic Transmission Service Requirement Prediction

Szabolcs Fischer István Lakatos Mykola Sysyn Dmytro Kurhan Szabolcs Kocsis Szurke Péter Ori

Publication Name: Infrastructures

Publication Date: 2023-02-01

Volume: 8

Issue: 2

Page Range: Unknown

Description:

Automatic transmission is a key factor for autonomous driving. The transmission condition is highly affected by the quality and quantity of transmission oil in the system. However, the oil condition is not monitored in the system, and the oil change interval and method are still a subject of discussion. This paper analyzes the effects of oil changes in automatic transmissions. The measurements were carried out before and after the oil change with the same external conditions. With the vibration measurement method, data can be collected without disassembling the parts and during operational conditions. Furthermore, time- and frequency-based analyses were conducted to compare different transmissions’ operations. The results have shown that the effect of oil degradation is measurable on the amplitude of the signals and, therefore, predictable with vibration diagnostics. During the evaluation, the maximum values were compared on measurements with at least a 2-s length.

Open Access: Yes

DOI: 10.3390/infrastructures8020031

Diagnostic measurement and data evaluation for the effective performance of motor vehicles with free acceleration

István Lakatos Péter Ori

Publication Name: Sisy 2017 IEEE 15th International Symposium on Intelligent Systems and Informatics Proceedings

Publication Date: 2017-10-23

Volume: Unknown

Issue: Unknown

Page Range: 219-224

Description:

During car services, it is sometimes necessary to measure the effective performance of the engines. After repairs it is very useful to check the change of the performance. In this case you don't have possibility of dismantling. You can measure the vehicle on roll benches. In this case you have so-called wheel performance as result. The new method discussed and described in this article provides a solution to this problem. The paper contains the theoretical and practical introduction of the measurement of engine performance with diagnostic measurement processes.

Open Access: Yes

DOI: 10.1109/SISY.2017.8080556

Diagnostic measurement for the effective performance of motor vehicles with free acceleration

István Lakatos Péter Ori

Publication Name: 15th Imeko Tc10 Workshop on Technical Diagnostics 2017 Technical Diagnostics in Cyber Physical Era

Publication Date: 2017-01-01

Volume: Unknown

Issue: Unknown

Page Range: 188-193

Description:

Diagnostics means instrumental measurement without dismantling. So measuring the engines on rolling roads is not incorporated in this concept, as this measurement is accomplished on engines taken out from vehicles. During service, it is often necessary to measure the performance of the engines, or to judge the performance projection of some corrections. The new method discussed in this article provides a solution to this problem.

Open Access: Yes

DOI: DOI not available