Automotive Vehicles Research Articles

EVALUATION OF TIMING CHAIN QUALITY AND ITS EFFECT ON TIMING SYSTEM OPERATION

Internal combustion engines are still the main source of propulsion for automotive vehicles. The timing system plays a very important role in the proper functioning of these engines. One of the widely used technical solutions to drive this system is the timing chain. However, in recent years, there has been a clear trend towards more frequent timing system failures. Many research works have focused on wear analysis or finite element method (FEM) modeling of chains. In contrast, it was decided to carry out a comparative study of the mechanical properties of new timing chains that are commercially available as spare parts for automotive workshops. The present study was carried out on timing system components of the popular Multijet 1.3 diesel engine used in Fiat, Opel, and Suzuki vehicles. Force-elongation curves were obtained for each of the tested chains, allowing their elongation under load to be estimated. In addition, breaking forces were measured, and breaking mechanisms were analyzed to compare the quality of the chains. Numerical parameters were proposed to estimate the quality of the tested chains. The chain tensioning forces resulting from the operation of the hydraulic tensioner were also estimated. The effect of the dynamic forces stretching the chain elastically on the timing accuracy during engine operation was also calculated.

The Influence of Problem-Solving Skills and Self-Efficacy on Learning Outcomes in Skills Concentration Subjects

This research is quantitative and aims to determine the impact of problem-solving skills and student self-efficacy on academic performance across various skill concentrations at SMK Negeri 1 Semen, Kediri Regency. The study focused on the subjects of Accounting (AKL), motorcycle engineering and business (TBSM), automotive light vehicle engineering (TKRO), and computer and network engineering (TKJ). Data collection involved questionnaires for assessing problem-solving skills and self-efficacy, while academic performance was measured through tests. The study included 185 students from all specialization concentrations at SMK Negeri 1 Semen, Kediri Regency. Data analysis utilized t-tests (partial test), f-tests (simultaneous test), and r2-tests or coefficient of determination tests. The research findings indicated that the significance level of the partial test for problem-solving skills was .002 < .050 and for self-efficacy was .003 < .050. The f-test revealed a significance value of .000 < .050. The results suggest that problem solving skills and self-efficacy significantly impact student academic performance across all skill concentrations, both individually and collectively.

ESTIMATION OF VEHICLE YAW SPEED USING PHOTOGRAMMETRY OF TIRE TRACKS AT TRAFFIC ACCIDENT SCENES

Background: This article presents a study on the use of photogrammetry to determine the critical yaw radius of automotive vehicles and, consequently, estimate the skidding speed. Photogrammetry is a non-invasive measurement technique that uses images to digitally reconstruct three-dimensional objects and analyse their geometric characteristics. Aim: The study aims to capture and process images of tire tracks from a vehicle in skidding conditions at the scene of a traffic accident to calculate the critical yaw radius and determine the skid speed. Methods: Images were rectified using specialized software and then processed to calculate the critical yaw radius, allowing the skid speed to be determined based on specific mathematical models. Results: The results obtained demonstrate the predictions and accuracy of photogrammetry as an effective tool for vehicle safety analysis and vehicle dynamics studies in skidding conditions. Discussion: This approach not only provides important information for the development of stability control systems, but also contributes to a deeper understanding of the specificities related to vehicle safety in critical driving situations. Conclusions: Photogrammetry proves to be a valuable method in enhancing vehicle safety analysis and understanding vehicle dynamics during skidding incidents.

USE OF UNMANNED TRANSPORTATION VEHICLES IN DELIVERY OF ROLLED METAL PRODUCTS AND NAVIGATION PROBLEMS

The article offers a comprehensive analysis of unmanned automotive vehicles in logistics, focusing particularly on the transportation of rolled steel products. It discusses key aspects of integrating and operating UAVs, highlighting their economic efficiency, safety, and environmental sustainability. Current safety issues in transporting rolled steel, including cargo securing methods and inertial force considerations, are thoroughly examined. Detailed insights into modern navigation technologies and safety systems like LiDAR and radars applied in unmanned vehicles are provided. Additionally, the article presents data on leading Russian companies in UAV development and implementation, such as Evocargo, KamAZ, SberAutoTech, and Starline, detailing their achievements and prospects in this field. Purpose. An investigation into the present status and future prospects of employing unmanned vehicles in logistics, with a specific focus on transporting rolled steel products. Methodology. Conducting an analysis of regulatory documents and standards, examining practical experience and case studies, performing a comparative analysis of navigation technologies, and engaging in theoretical analysis and synthesis. Results. For successful integration of unmanned vehicles into the delivery of rolled steel products, it is recommended to launch pilot projects on key routes, develop infrastructure for charging and refueling stations, establish regulatory frameworks, and collaborate with industry partners. Practical implications. The results are advantageous for entities engaged in the logistics and transportation of rolled steel products. Integrating unmanned vehicles can enhance delivery efficiency and safety, as well as reduce CO₂ emissions, which are critical for sustainable development and cost reduction.

Ti-alloyed β-W heterojunctions exhibiting spin-orbit torque switching at a wide operating temperature range

Spin-orbit torque (SOT) switching has gained significant interest, particularly in the context of non-volatile embedded memory for advanced automotive vehicles. The study of temperature-dependent SOT switching, a less explored area, is crucial for developing automotive electronics Grade-0, which requires an ambient operating temperature range from −40 to 150 °C. These SOT devices demand substantial SOT efficiency to ensure a low operating current. Additionally, materials employed in these devices must be compatible with semiconductor fabrication. This study presents the first principles calculations to estimate the spin Hall conductivity (σSH) change of Ti-alloyed β-phase W structures depending on the Ti composition. The calculation predicts the highest σSH value of −1461 (ℏ/e) S/cm at Ti 12.5 at%. In addition, we fabricate β-W-Ti (x at%) 5/Co40Fe40B20 0.9/MgO 1 (in nm) heterojunctions with various Ti compositions to confirm the above result experimentally. Under the controllable experimental condition, we observe the heterojunction with β-W-Ti 11.5 at% exhibits an enhanced damping-like SOT efficiency of 0.54 (compared to 0.30 of pure β-W) with longitudinal resistivity of 149.7 μΩ·cm. The critical current density (Jc) reaches as low as 15.5 cm2. We also demonstrate that SOT switching is possible at ambient temperatures ranging from −55 to +150 °C.

Cybersecurity Maintenance in the Automotive Industry Challenges and Solutions: A Technology Adoption Approach

Numerous attempts have been made to create a secure system that meets the criteria and requirements of the automotive vehicle development life cycle. However, a critical gap exists in the secure development lifecycle, particularly concerning the development and maintenance of software after the vehicle has been sold by the manufacturer. This step is often overlooked by original equipment manufacturers (OEMs), especially after the expiration of the vehicle warranty period, given the cost that it will require to update and test the software in their vehicles. This paper addresses the issues that affect current and future vehicle cybersecurity, during the maintenance of cybersecurity, and how the neglect of it could end up creating hazards for the vehicle owner or other road users. To accomplish this, we will employ the technology adoption model (TAM) as a theoretical framework, which is used to understand and predict how organizations adopt technology. Thus, through qualitative and quantitative research, including text mining, we identify the challenges in the adoption and diffusion of cybersecurity maintenance in the automotive sector and its supply chain. In addition, we propose possible solutions on how to maintain a level of security that will benefit road users, OEMs and regulators, covering the cybersecurity needs for the vehicle’s usable life, taking into account the vehicle’s heterogeneity of components and technology, connectivity, environmental impact and cost of production and maintenance of a vehicle.

Evaluation of three kinetic energy storage systems

Abstract. This paper investigates recent advances in energy recovery systems (ERS) in automotive vehicles to reduce air pollution and impact on climate change. The three ERS systems: mechanical flywheel, regenerative braking, and regenerative electrically assisted (REAT) turbocharger are evaluated for their potential to reclaim energy wasted by the automobile thereby increasing range and efficiency of the vehicle. The methods of comparison are based on data sourced from current literature relevant to total energy recovery, system configuration, and application feasibility. This will identify regenerative braking as best for new vehicles to decrease fuel consumption and regenerative electrically assisted turbocharges (REAT) as best for retrofitting older vehicles. The paper will use the results to identify the energy recovery system with the greatest potential for immediate application and further research to overcome remaining challenges.

A review of the application development and key technologies of rotary engines under the background of carbon neutrality

Rotary engines possess advantages such as light weight, high power density, and strong fuel adaptability, which are essential for powertrain systems. They hold great potential in the field of power machinery. However, the development of rotary engines has been constrained by increasingly stringent emission regulations. Despite this, numerous scholars and institutions continue to optimize rotary engines, leading to a proliferation of related research. It is necessary to synthesize these findings to guide future promotion and application efforts. This review examines the current applications and development status of rotary engines globally. It summarizes the development of key technologies such as sealing techniques, rotor configurations, and ignition devices, which have achieved lower energy consumption and emissions. The suitability of rotary engines for automotive and unmanned aerial vehicle applications has also been reported. To further reduce carbon emissions, researchers have explored zero-carbon fuel rotary engines. Hydrogen-fueled rotary engines have demonstrated higher combustion efficiency. By integrating EGR, load control strategies, and ignition system layouts, they have addressed issues such as NOx emissions, knock, and leakage. The development of ammonia-hydrogen hybrid fuels is also a potential effective solution. Continuous innovative research indicates that, with their inherent advantages and the integration of alternative fuels and advanced ignition technologies, rotary engines have the potential to meet future energy and environmental requirements. This positions them as strong contenders in future diversified power systems.

Intrusion detection using metaheuristic optimization within IoT/IIoT systems and software of autonomous vehicles

The integration of IoT systems into automotive vehicles has raised concerns associated with intrusion detection within these systems. Vehicles equipped with a controller area network (CAN) control several systems within a vehicle where disruptions in function can lead to significant malfunctions, injuries, and even loss of life. Detecting disruption is a primary concern as vehicles move to higher degrees of autonomy and the possibility of self-driving is explored. Tackling cyber-security challenges within CAN is essential to improve vehicle and road safety. Standard differences between different manufacturers make the implementation of a discreet system difficult; therefore, data-driven techniques are needed to tackle the ever-evolving landscape of cyber security within the automotive field. This paper examines the possibility of using machine learning classifiers to identify cyber assaults in CAN systems. To achieve applicability, we cover two classifiers: extreme gradient boost and K-nearest neighbor algorithms. However, as their performance hinges on proper parameter selection, a modified metaheuristic optimizer is introduced as well to tackle parameter optimization. The proposed approach is tested on a publicly available dataset with the best-performing models exceeding 89% accuracy. Optimizer outcomes have undergone rigorous statistical analysis, and the best-performing models were subjected to analysis using explainable artificial intelligence techniques to determine feature impacts on the best-performing model.

Electromechanical processes in electric power steering system based on permanent magnet synchronous motor

Relevance. Electric power steering of vehicles successfully competes with hydraulic boosters of similar purposes, showing high efficiency, energy saving and environmental friendliness. Aim. To study and research electromechanical processes of electric power steering system based on permanent magnet synchronous motor. Methods. Mathematical and numerical modeling using the Matlab/Simulink software package. Results. The article discusses the operating modes of an electric power steering based on an electric motor with permanent magnets. The authors analyzed two classic schemes for constructing steering systems with electric power steering – with the electric motor placed on the steering column and on the steering rack. Block diagrams of the mechanical and electrical parts of the steering system have been developed. Based on mathematical dependencies characterizing the operating modes of the steering system, a complete dynamic simulation model of the electric power amplifier was obtained on the MATLAB/Simulink platform. Based on a preliminary analysis of control methods and algorithms in the system to solve the problem of control stability, PI controllers with low-pass filters are implemented to regulate the current and voltage of the electric motor depending on the speed of the vehicle and the angle of rotation of the steering wheels. The simulation results were used to design a real electric power steering for a specific vehicle. Conclusions. The complete simulation model of an electric booster based on a synchronous motor with permanent magnets in a car steering system obtained by the authors adequately reflects the dynamic control processes and can be used in the design of automotive vehicles.

Unlocking the Green Potential: Assessing the Role of Green Hydrogen in Revolutionizing Electricity Generation and Fueling Automotive Vehicles (FCEVS)

Unlocking the Green Potential: Assessing the Role of Green Hydrogen in Revolutionizing Electricity Generation and Fueling Automotive Vehicles (FCEVS)

RFSoC Softwarisation of a 2.45 GHz Doppler Microwave Radar Motion Sensor

Microwave Doppler sensors are used extensively in motion detection as they are energy-efficient, small-size and relatively low-cost sensors. Common applications of microwave Doppler sensors are for detecting intrusion behind a car roof liner inside an automotive vehicle and to detect moving objects. These applications require a millisecond response from the target for effective detection. A Doppler microwave sensor is ideally suited to the task, as we are only interested in movement of a large water-based mass (i.e., a person) (FMCW Radar also detect static objects). Although microwave components at 2.45 GHz are now relatively cheap due to mass production of other Industrial Scientific and Medical application (ISM) devices, they do require tuning for temperature compensation, dielectric, and manufacturing variability. A digital solution would be ideal, as chip solutions are known to be more repeatable, but Application-Specific Integrated Circuits (ASICs) are expensive to initially prototype. This paper presents the first completely digital Doppler motion sensor solution at 2.45 GHz, implemented on the new RFSoC from Xilinx without the need to up/downconvert the frequency externally. Our proposed system uses a completely digital approach bringing the benefits of product repeatability, better overtemperature performance and softwarisation, without compromising any performance metric associated with a comparable analogue motion sensor. The RFSoC shows to give superior distance versus false detection, as the Signal-to-Noise Ratio (SNR) is better than a typical analogue system. This is mainly due to the high gain amplification requirement of an analogue system, making it susceptible to electrical noise appearing in the intermediate-frequency (IF) baseband. The proposed RFSoC-based Doppler sensor shows how digital technology can replace traditional analogue radio frequency (RF). A case study is presented showing how we can use a novel method of using multiple Doppler channels to provide range discrimination, which can be performed in both analogue and in a digital implementation (RFSoC).

Optimization strategies for enhancing diesel engine performance and emissions control with biofuel blends: A multi-objective approach

This study examines the effects of engine compression ratio, load, and biofuel composition on performance, combustion, and emissions. The experimental setup includes testing different compression ratios (16, 17, 18) and loads (25 %, 50 %, 75 % torque) at a fixed speed of 1500 rpm, using Thai standard diesel as the control fuel. Biofuel variations tested include neat biodiesel, neat biokerosene, and blends of 30 % biokerosene with 70 % biodiesel and 50 % biokerosene with 50 % biodiesel. The results show that an increased compression ratio enhances combustion efficiency, reduces brake specific fuel consumption, and improves brake thermal efficiency, although it also leads to higher nitrogen oxide emissions. Biofuels improve brake thermal efficiency due to their higher oxygen content. However, the increased viscosity of biodiesel can hinder fuel atomization, resulting in higher emissions. In contrast, biokerosene improves brake thermal efficiency by facilitating earlier combustion and reducing emissions. Performance is primarily affected by load, while emissions are influenced by both biokerosene content and load. Gradient boosting models and optimization techniques, such as the non-dominated sorting genetic algorithm III (NSGA-III) and adaptive geometry estimation-based multi-objective evolutionary algorithms (AGE-MOEA), produce consistent results, with AGE-MOEA identifying denser optimal points. The findings suggest that optimal biokerosene blends ranging from 20 % to 40 %, across all compression ratios and loads of 50 %–75 %, provide valuable insights for advancing sustainable fuel utilization practices in automotive vehicles.

Analysis of glass fiber-reinforced composite leaf springs in a light commercial vehicle

Leaf springs are designed to bear loads as well as shocks in automotive vehicles. Two leaves of glass fiber-reinforced composites (GFRCs) of various shapes sandwiched between steel plates were analyzed for application in a minitruck. Computer-aided engineering analysis was performed for five different types of GFRC material leaf springs: flat leaf, flat and parabolic leaf, both parabolic leaf, both parabolic leaf springs with aluminium alloy bushes at the eye-end and spring steel multi-leaf springs. A silencer pad was used in the parabolic leaf spring to reduce delamination and vibration at contact points of the mating leaf. The various shapes and combinations of leaves provided varying parameters, namely, the deformation, maximum equivalent strain, maximum equivalent stress and fatigue life. The CAE results showed that compared with the other combinations, the flat leaf and parabolic leaf combinations provided the maximum equivalent strain, maximum equivalent stress and fatigue life.

Comparative performance and emission analysis of internal combustion engine and battery electric vehicle under modified Indian drive cycle

This study deals with an analysis of the performance and emissions characteristics of an automotive Compression Ignition Engine Vehicle (CIEV) with 86 kW rated power output fueled with diesel in comparison to a grid based Battery Electric Vehicle (BEV) with 86 kW Electric Motor under the Modified Indian Drive Cycle (MIDC) using the simulation. A novel methodology for undertaking the comparative analysis is developed to assess the CIEV and BEV performance for different scenarios under wide operating conditions. The results indicate that energy consumptions for CIEV and BEV under the MIDC cycle are 2653.1 kJ/km and 416.72 kJ/km. The net effective carbon price during fuel production and vehicle operation is Rs 0.20 per km for CIEV which is 80 % more than Rs 0.11 per km for BEV. A BEV also has an initial carbon debt due to battery production which is 27 times that of CIEV, however, this penalty is easily recovered within a short period against the lower running costs of BEV. The range of the ICE power source is estimated to be 5.85 times that of the EV for MIDC. By increasing the battery capacity five fold, the range of EV can be enhanced, however considerable weight penalty is levied. The levelised cost of transportation for one lakh kilometers was assessed wherein it was found that ICE vehicle expenditure is approximately Rs 25.59 per km against Rs 23.31 per km of BEV.

Design of an Embedded System based on strain gauges to mitigate automotive vehicle thefts, Lima 2023

Design of an Embedded System based on strain gauges to mitigate automotive vehicle thefts, Lima 2023

Integrating Topographical Map Information in SUMO to Simulate Realistic Micromobility Trips in Hilly and Steep Terrains

Nowadays, shared micromobility has become a trend in cities as an alternative to conventional automotive vehicles, especially for short-distance travel. It also plays an important role in the reduction of the number of automotive vehicles which results in a decrease of air pollution and traffic congestion. Shared micromobility is, however, influenced by the terrain characteristics. Varying elevation within a fleet operational area can cause imbalances in the use of micromobility stations if a steep terrain lies between stations. It also impacts the energy consumption of electric micromobility vehicles such as e-bicycles and e-scooters. Therefore, to simulate the state of charge (SOC) of traction batteries for micromobility close to reality, it is essential to include elevation data into the simulation model. This paper proposes a workflow for Simulation of Urban MObility (SUMO) comprising several steps with concrete implementation and validation in order to prepare and define the simulation model with micromobility stations and the integration of elevation data using a REST API. The integration of elevation and bike station data is validated with a defined vehicle type following a route in the hilly part of Stuttgart, Germany. A comparison of micromobility trips, with and without elevation data, was performed through a simulation by recording changes in energy consumption and driven altitude differences. The proposed workflow provides a basis for more complex use cases such as analysing micromobility business areas, improving vehicle.

Integrated catalytic systems for simultaneous NOx and PM reduction: a comprehensive evaluation of synergistic performance and combustion waste energy utilization.

The global transition towards sustainable automotive vehicles has driven the demand for energy-efficient internal combustion engines with advanced aftertreatment systems capable of reducing nitrogen oxides (NOx) and particulate matter (PM) emissions. This comprehensive review explores the latest advancements in aftertreatment technologies, focusing on the synergistic integration of in-cylinder combustion strategies, such as low-temperature combustion (LTC), with post-combustion purification systems. Selective catalytic reduction (SCR), lean NOx traps (LNT), and diesel particulate filters (DPF) are critically examined, highlighting novel catalyst formulations and system configurations that enhance low-temperature performance and durability. The review also investigates the potential of energy conversion and recovery techniques, including thermoelectric generators and organic Rankine cycles, to harness waste heat from the exhaust and improve overall system efficiency. By analyzing the complex interactions between engine operating parameters, combustion kinetics, and emission formation, this study provides valuable insights into the optimization of integrated LTC-aftertreatment systems. Furthermore, the review emphasizes the importance of considering real-world driving conditions and transient operation in the development and evaluation of these technologies. The findings presented in this article lay the foundation for future research efforts aimed at overcoming the limitations of current aftertreatment systems and achieving superior emission reduction performance in advanced combustion engines, ultimately contributing to the development of sustainable and efficient automotive technologies.

STRIDE-Based Cybersecurity Threat Modeling, Risk Assessment and Treatment of an In-Vehicle Infotainment System

In modern automobiles, the infotainment system is crucial for enhancing driver and passenger capabilities, offering advanced features such as music, navigation, communication, and entertainment. Leveraging Wi-Fi, cellular networks, NFC, and Bluetooth, the system ensures continuous internet connectivity, providing seamless access to information. However, the increasing complexity of IT connectivity in vehicles raises significant cybersecurity concerns, including potential data breaches and exposure of sensitive information. To enhance security in infotainment systems, this study applied component-level threat modeling to a proposed infotainment system using the Microsoft STRIDE model. This approach illustrates potential component-level security issues impacting privacy and security concerns. The study also assessed these impacts using SAHARA and DREAD risk assessment methodologies. The threat modeling process identified 34 potential security threats, each accompanied by detailed information. Moreover, a comparative analysis is performed to compute risk values for prioritizing treatment, followed by recommending mitigation strategies for each identified threat. These identified threats and associated risks require careful consideration to prevent potential cyberattacks before deploying the infotainment system in automotive vehicles.

Development of Student Worksheets based on the Discovery Learning Approach in the Automotive Light Vehicle Engineering Program at Vocational High Schools

This research aims to develop student worksheets based on the discovery learning approach. Designing Student Worksheets based on the discovery learning approach for class x automotive light vehicle engineering at state vocational high school 1 Seunuddon. Vocational Education Study Program in Mechanical Engineering fakultas keguruan dan ilmu pendidikan Malikussaleh University, 2024. This research aims to describe the design, feasibility and learning outcomes of class automotive. This research uses a mix methods approach. This research used a sample consisting of 8 class X students majoring in automotive engineering. Data collection uses questionnaires, documentation, interviews and observations, data analysis techniques use percentage qualitative analysis through data collection and drawing conclusions. The research results show student learning outcomes. The media I results gave an overall score with a percentage of 89.28% and media experts II gave an overall score with a percentage of 89.28%. The average percentage of the two validators shows the "very feasible" category. Thus, this student worksheet is very suitable for usefor learning by teachers and students. Where the value obtained has passed the learning objective achievement criteria value which has been determined as a reference for the success of the learning process at 75 with a percentage of 78.75%, thus it can be concluded that the value obtained by the students is categorized as complete. Thus, this student worksheet is suitable for use by teachers and students for a more effective learning process.