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Found 6383 publications

Possibilities for Further Development of the Airbags in the Case of Non-conventional Seating Positions

I. Lakatos Laszlo Porkolab

Publication Name: Periodica Polytechnica Transportation Engineering

Publication Date: 2025-01-01

Volume: 53

Issue: 2

Page Range: 146-157

Description:

The first ideas and experiments aimed at protecting passengers from the vehicle’s internal components with airbags date back to the 1960s. Twenty years later, the airbag appeared in series production, in December 1980, the Mercedes-Benz S-Class (W126) was the first serial production car to be equipped with a driver airbag, and since its introduction, the use of airbag technology has been uninterrupted. Airbag systems are currently regarded as almost mandatory protection systems in a vehicle. The article generally presents the development of airbags used in cars, followed by the currently used airbag folding types. After that, the article presents the simulation of the airbag deployment, its types and theoretical background, as well as the most important stages of the deployment of the airbag. In the following, the article presents the results of the research so far in the case of frontal and side crashes. The next section of the article introduces the materials capable of absorbing energy, then details the simulation model built and the airbag concept created. The last part of the article contains an evaluation of the results and the summary. The modified seat examined in the earlier phase of the research and the airbag concept that is the subject of this research also fulfill the set goals, but the latter has a great advantage.

Open Access: Yes

DOI: 10.3311/PPtr.38633

N-best Design Options with Strategical Differences in Process Network Synthesis

Ákos Orosz Sin Yong Teng Ferenc Friedler

Publication Name: Chemical Engineering Transactions

Publication Date: 2025-01-01

Volume: 120

Issue: Unknown

Page Range: 409-414

Description:

The main goal of Process Network Synthesis is usually to find the lowest-cost process for a given problem. Since the model is not able to account for every parameter of an industrial realisation, the decision makers prefer to have alternatives, which can be provided when generating the n-best solutions. This, however, comes with another issue, specifically that several of the near-optimal solutions are almost identical to the optimal one, and only differ in one or two operating units. Thus, the next step to improve the generation of feasible and performant alternatives is to provide process designs with meaningful differences from the optimum. Meaningful differences between designs have to be defined by the decision makers. These are differences that the decision makers consider as major strategic questions, while other changes in the process constitute fine details where simply selecting the lowest cost option is enough. The current work describes a branch-and-bound algorithm that is able to generate the n-best strategically different process designs. The difference between considering and ignoring strategic differences when generating n-best solutions is illustrated via a case study.

Open Access: Yes

DOI: 10.3303/CET25120069

Edge AI Benchmarking: Tools, Methodologies, and Optimization Strategies, a review

Sandor R. Repas Mustafa Abdulkadhim

Publication Name: International Conference on Electrical Computer and Energy Technologies Icecet 2025

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Edge computing has emerged as an important paradigm to address the evolving demands of latency-sensitive applications and the adaptation of Internet of Things (IoT) devices, offering near edge data processing to increase performance, reduce bandwidth usage, and increase data privacy. However, benchmarking these heterogeneous edge environments remains a challenge due to their distributed nature and diverse hardware configurations. This paper proposes "Scalable Heterogeneous Edge Automation Benchmarking"(SHEAB), a novel containerized and automated framework designed to evaluate edge computing systems comprehensively. SHEAB integrates containerization for portability, automation for efficiency, and a multi-layered security architecture - including firewalls, VPNs, and secure shell connections - to ensure robust data integrity across varied edge servers. This research advances the field by providing a scalable, secure, and adaptable benchmarking solution, with future directions aimed at researching hardware capability assessments and increasing AI-driven edge-computing testing and benchmarking.

Open Access: Yes

DOI: 10.1109/ICECET63943.2025.11472323

Sustainability in Manufacturing: MILP Models of a Production Line Optimization Problem

Tamás Hajba

Publication Name: Chemical Engineering Transactions

Publication Date: 2025-01-01

Volume: 121

Issue: Unknown

Page Range: 55-60

Description:

In modern factories, the optimization of production lines is essential to reduce energy consumption and costs. A well-known model of production line optimization is the Permutation Flow Shop Problem (PFSP) with makespan minimization. PFSP instances arising in industry often have some special features: the problem may contain jobs whose processing times are equal on every machine. Such jobs are said to be of the same type. Due to technological reasons, some of the permutations may be forbidden. For example, only those job permutations are allowed in which, for each job type, the length of a maximal block of jobs from that type is divisible by a prescribed number (the lot size of that type). Considering these features, this paper introduces a generalization of the Permutation Flow Shop with Repetition and Lot Size Problem, in which different types of jobs have different lot sizes. We present two new mixed integer linear programming formulations of the problem and compare their effectiveness on a set of benchmark problems. Both models found the optimal solution within a few seconds for all problem instances involving 10 machines, 100 jobs, and five different types. These results show that even large-scale problems containing a small number of different jobs can be solved using these models.

Open Access: Yes

DOI: 10.3303/CET25121010

Inductive vs. Deductive Learning in Calculus: Unraveling the Impact on Integral Understanding

Nárcisz Kulcsár

Publication Name: Sefi 2025 53rd Annual Conference of the European Society for Engineering Education Engineering and Society Proceedings

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 579-587

Description:

Our experience of learning mathematics in schools is often based on learning and applying formulas. This suggests that teaching follows a predominantly deductive approach in which students use predetermined rules and theorems to solve problems. This is the dominant method worldwide, but the question arises: is it possible to teach mathematics in other ways, for example by an inductive approach, which first introduces students to general relationships by starting with concrete examples? The aim of this study was to evaluate the effectiveness of both inductive and deductive learning methods in engineering mathematics education. The experimental group learned the basics of integration through group work using either an inductive or a deductive approach. Their acquired knowledge was assessed through a test, which was repeated one week later. Following the learning process, they also completed a questionnaire in which they described their learning experience, strengths, and challenges. The results indicate that both methods have advantages and challenges with no significant difference in overall effectiveness based on test scores. Students generally reported positive experiences, but some suggested improvements such as restructuring group sizes, providing a mix of both methods, and increasing opportunities for cross-group discussions. Overall, the findings suggest that integrating elements of both learning approaches could offer a more balanced approach, catering to different learning styles while maintaining engagement and conceptual clarity.

Open Access: Yes

DOI: 10.5281/zenodo.17632066

Impact of measurement and test parameters on the rpm-sweep test accuracy of e-motors

Balázs Vehovszky Zoltán Gazdagh D. Acs

Publication Name: 54th International Congress and Exposition on Noise Control Engineering Internoise 2025

Publication Date: 2025-01-01

Volume: 4

Issue: Unknown

Page Range: 70-77

Description:

The electrification of the vehicle industry has led to a significant increase in the demand for innovative vibration testing. The RPM-sweep experiments of e-motors and e-drives are considered to be fundamental, as they provide valuable vibration and durability data for further analysis. The aim is to model the behavior of rotating-dynamic systems throughout their life cycles. However, inaccuracies in the definition of measurement and test parameters can result inaccurate transfer functions, ultimately reducing the accuracy and reliability of the test results. This paper focuses on two critical parameters: frequency resolution and RPM-sweep rate. Both of these parameters have a significant impact on the amplitude response of the system and can lead to substantial distortion of the FRFs. In this study, we characterize these distortions and propose a method to ensure that the error introduced by the chosen frequency resolution and RPM-sweep rate remains below a predefined threshold value. In addition to the theoretical derivation, we demonstrate the application of this method using real measurement data. This research aims to address the challenges associated with NVH testing in the context of the electrification of the vehicle industry, providing a valuable contribution to the development of more accurate and reliable testing methodologies.

Open Access: Yes

DOI: 10.3397/IN_2025_1062472

Driver Focused Comparison of Field Oriented Control and Direct Torque Control using MATLAB Simulink Simulations

Istvan Szalay Tamás Horváth Denes Fodor

Publication Name: Edpe 2025 37th International Conference on Electrical Drives and Power Electronics and 12th Joint Croatia Slovakia Conference

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper presents a comparison of two widely used motor control strategies namely field oriented control (FOC) and direct torque control (DTC). They both have their advantages and disadvantages that make them a suitable choice for use in a vehicle drive system. This paper compares these two implemented in a MATLAB Simulink simulation using an automotive Permanent Magnet Synchronous Motor (PMSM). The motor and test parameters are chosen to be realistic from a human driver point-ofview. Simulation results are analyzed to highlight the differences between the two strategies and identify cases where one outperforms the other. In conclusion, the paper shows the effects of the differences and the general characteristics of the simulation results in a realistic case on a human driver as the user of the PMSM in an automotive drive. The paper contributes valuable insight in the classic comparison of these two strategies for automotive use.

Open Access: Yes

DOI: 10.1109/EDPE66853.2025.11224164

Real-Time Out of Distribution Detection in 2D Object Detection for Autonomous Cars

Andrea Ádámné Major Zoltán Weltsch Lóránt Szabó

Publication Name: Engineering Perspective

Publication Date: 2025-01-01

Volume: 5

Issue: Special-Issue

Page Range: 28-35

Description:

The development of autonomous transportation systems represents a critical step toward achieving intelligent and reliable mobility. Ensuring accurate, real-time environmental perception and the robust detection of unexpected or rare events remains a major challenge for autonomous vehicles operating in complex and dynamic environments. To address this, we propose a novel processing pipeline that constructs Bird’s Eye View (BEV) representations from raw 3D LiDAR point clouds using both intensity and height map channels, thereby retaining essential geometric and reflective features. On top of these BEV representations, an optimized YOLOv11-based deep learning model is applied for high-precision object detection. A key contribution of our work is the integration of a real-time Out-of-Distribution (OOD) detection module, which employs lightweight statistical techniques in conjunction with learned feature representations to ensure minimal computational overhead while maintaining operational robustness. The proposed architecture enables the reliable identification of standard traffic objects as well as the detection of atypical or previously unseen events, such as overturned vehicles or unknown obstacles. Experimental evaluation on representative driving scenarios demonstrates that our method achieves approximately 95% detection accuracy, outperforming conventional baselines in both speed and reliability. Overall, the results highlight the potential of combining state-of-the-art deep neural detection frameworks with efficient, statistically grounded OOD analysis for enhancing the safety and trustworthiness of autonomous vehicle perception systems.

Open Access: Yes

DOI: 10.64808/engineeringperspective.1814718

Validation of the Energy Consumption of an Electric Vehicle System Model in the 3D Environment of the High-Speed Handling Module of the ZalaZONE Automotive Proving Grounds †

József Gábor Pázmány Árpád Török Emil Nagy

Publication Name: Engineering Proceedings

Publication Date: 2025-01-01

Volume: 113

Issue: 1

Page Range: Unknown

Description:

Contemporary research on electric vehicle (EV) consumption is predominantly focused on the vehicle’s powertrain and battery technology. However, the analyses indicate that the actual state of the various electrical subsystems in the vehicle can have a significant impact on the overall consumption figures. The primary objective of this article is to demonstrate the capabilities of our vehicle simulation model, which was developed with a particular focus on the electrical subsystems of vehicles, when employed in a 3D digital representation of a real environment. The central scientific contribution of this work is the systematic quantification of subsystem-level energy usage in real-world scenario simulation. This provides a novel framework for the evaluation of EV energy distribution, thereby informing future strategies and models.

Open Access: Yes

DOI: 10.3390/engproc2025113004