Vehicle Manufacturers Research Articles

Model-based definition-assisted asset administration shell as enabler for smart production line

ABSTRACT The smart production line needs to adapt continuously to satisfy the growing demand for customized products. However, the inability of equipment to interoperate effectively hampers the quick reconfiguration of smart production lines. The Reference Architecture Model for Industry 4.0 (RAMI4.0) introduces the Asset Administration Shell (AAS) as a novel method to enhance interoperability in Industry 4.0 (I4.0). AAS creates a digital representation of assets. To further enhance the efficiency of AAS configuration, this paper presents the Model-Based Definition (MBD)-assisted AAS (MBD-AAS) specifically for designing smart production lines. MBD-AAS streamlines AAS configuration and facilitates plug-and-play (PnP) capabilities for equipment in smart production lines. This study validates the practicality and advantages of MBD-AAS through a case study focused on an unmanned aerial vehicle (UAV) production line design. The experimental findings indicate that MBD-AAS enhances the interoperability of AAS and decreases the design time for UAV production lines.

Research on the Impact of Fiscal Subsidies on High-Quality Development of New Energy Vehicle Companies Based on Threshold Effects

In recent years, China has made significant strides in developing the new energy vehicle industry, providing substantial financial support to this sector. The production and sales of new energy vehicles have experienced explosive growth, accompanied by notable improvements in technology and product quality. However, as the industry evolved, the effectiveness of financial subsidies in enhancing the production and technological capabilities of enterprises has gradually diminished. To foster the rapid development of new energy vehicle enterprises and facilitate the rational planning of relevant government financial subsidies, this study utilizes data from listed Chinese new energy vehicle companies spanning from 2017 to 2022 to investigate the intrinsic relationship between financial subsidies and the quality development of enterprises. The study reveals several key findings. First, when fiscal subsidies are maintained within a reasonable range, they significantly enhance the quality development of state-owned enterprises (SOEs). However, once this threshold is surpassed, further increases in fiscal subsidies do not promote quality development of enterprises, a phenomenon that does not apply to non-state enterprises. Second, the threshold effect of financial subsidies on quality development is particularly pronounced between newly listed companies and those listed for more than three years. Third, for SOEs, financial subsidies play a critical role in fostering high-quality development by boosting R&D investment; this relationship is not observed in non-SOEs. Consequently, this study advocates the establishment of differentiated financial support policies for the new energy vehicle industry to maximize their effectiveness.

The Role of Technical Car Features in Managing and Promoting New Peer-to-Peer Car-Sharing Systems: Insights from Potential Users and Strategic Implications for Service Providers

Peer-to-peer car-sharing systems are an evolving branch of urban mobility, aligning with global trends focused on sustainable development and reducing congestion in cities. A research gap has been identified concerning the specific vehicle attributes that would encourage the public to potentially use these services. Addressing this gap, and in the context of launching a new peer-to-peer car-sharing service in Katowice, Poland, this article investigates the technical features influencing the choice of vehicles in peer-to-peer car-sharing systems, particularly from the perspective of individuals who currently do not use such platforms. The study employs Social Network Analysis (SNA) to examine the interrelationships between vehicle attributes. The analysis reveals that key factors influencing users’ decisions include fuel/energy consumption, safety features, and technological advancement, with a particular emphasis on driver assistance systems, including autonomous driving capabilities. The network structure, characterized by a relatively low density (0.2536) and a short average path length (1.872), suggests that a few central vehicle features dominate user decisions, and improvements in these key areas can quickly propagate through the decision-making process, enhancing overall user satisfaction. To validate the findings, a Gradient Boosting Regression (GBR) analysis was conducted, confirming the significance of the key factors identified by the SNA, such as fuel efficiency, battery capacity, and safety systems, thus strengthening the reliability of the results. This study underscores the growing importance of sustainability and technological innovation in the automotive industry, particularly in the context of the sharing economy. It suggests that car-sharing platforms and vehicle manufacturers should prioritize these features to meet user expectations and preferences. These findings provide valuable insights for the strategic and operational management of peer-to-peer car-sharing services, emphasizing the importance of targeted vehicle selection and user-centered innovations to improve platform performance and scalability.

Feδ+ diaspora titanium dioxide and graphene: A study of conductive powder materials and coating applications.

Developing new conductive primers to ensure electrostatic spraying is crucial in response to the call for lightweight production of new energy vehicles. We report a stabilized material, Fe-T/G, of Fe-doped TiO2 composite graphene synthesized by a simple hydrothermal and electrostatic self-assembly method. The resistivity decreases from 0.9165Ω·cm to 0.0943Ω·cm for T/G. XPS and EPR confirm that Fe3+ is doped into the TiO2 lattice to generate OVs, and Feδ+ is introduced to activate the surrounding Fe-Ti active sites to break the obstruction of the Ti-O bond and build the Ti-O-C and Feδ+-O-C bonds between TiO2 and graphene to connect the two tightly. Multiple electron transfer channels promote Feδ+ impurity energy levels in the TiO2 valence and conduction bands to build electron leaping pathways, enhancing the electron transport ability. Based on this, Fe-T/G can be used as a conductive coating material to develop various insulator surfaces. With Fe-T/G powder material and PVDF, a conductive primer coating can be made and overlaid on a plastic plate to simulate actual applications. The resistance can still be maintained below 25Ω·cm. Through contact angle experiments, it has been confirmed that the superhydrophobic surface has a water contact angle of 142.8°, with self-cleaning potential.

Predictive Analytics in Vehicle Manufacturing: Enhancing Engine Performance and Operational Efficiency in Modern Automotive Plants

Predictive Analytics in Vehicle Manufacturing: Enhancing Engine Performance and Operational Efficiency in Modern Automotive Plants

Planet 2050 and the Future of Manufacturing: Data-Driven Approaches to Sustainable Production in Large Vehicle Manufacturing Plants

Planet 2050 and the Future of Manufacturing: Data-Driven Approaches to Sustainable Production in Large Vehicle Manufacturing Plants

Dynamic Optimization of Vehicle Production Planning in Transportation Networks Using Federated Reinforcement Learning

Dynamic Optimization of Vehicle Production Planning in Transportation Networks Using Federated Reinforcement Learning

Collaborative management of battery manufacturer responsibility in electric vehicle production with ESG due diligence

Collaborative management of battery manufacturer responsibility in electric vehicle production with ESG due diligence

Optimizing electric vehicle charging strategies using multi-layer perception-based spatio-temporal prediction of charging station load

The production and sales of electric vehicles have been increasing in line with the gradual adaptation of consumers to electric vehicles, driven by various government policies and subsidies over the past decade. As a result, the deployment of charging facilities, which are essential for supporting electric vehicles, has also been extensive. However, despite the rapid development in scale, charging facilities face challenges such as low utilization during off-peak hours and excessive congestion during peak hours, leading to resource wastage and a diminished user charging experience. To address these issues, this study proposes a spatio-temporal prediction model for charging station load. The model introduces a global spatial enhancement module to simultaneously learn short-range and long-range spatial dependencies in the data, resulting in improved prediction accuracy. The aim of this research is to provide practical guidance in terms of conserving charging resources and enhancing user charging experience based on spatio-temporal prediction effectiveness.

REMAINING USEFUL LIFE PREDICTOR FOR EV BATTERIES USING MACHINE LEARNING

Electric vehicles (EVs) are a key solution to combat rising carbon emissions and reduce dependence on fossil fuels. In India, the government has implemented policies such as the Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME) scheme to promote EV adoption Predicting the Remaining Useful Life (RUL) of EV batteries using machine learning ensures better battery health management and enhances operational efficiency. Applications include EV fleet management, battery recycling, and cost-effective maintenance. To develop a machine learning model that accurately predicts the Remaining Useful Life (RUL) of EV batteries to improve operational reliability, reduce maintenance costs, and support sustainable energy practices. Before the advent of machine learning, traditional methods for estimating EV battery life relied on rule-based approaches, where predefined thresholds such as voltage drops or charge cycles were used to predict battery health. Empirical models, often linear, were developed based on historical performance data but lacked the ability to adapt to dynamic usage patterns. Additionally, manual battery testing was a common practice to measure degradation, though it was time-consuming, labor-intensive, and often prone to inaccuracies in capturing the complex nature of battery aging. Traditional systems for predicting EV battery life are largely empirical and rely on static models that fail to capture dynamic battery behavior. These methods often lack precision, are labor-intensive, and provide limited adaptability to varying usage conditions, leading to inefficiencies in battery management. The increasing demand for EVs and their critical dependence on battery performance drives the need for accurate RUL prediction systems. Traditional methods are insufficient in addressing the complex, non-linear nature of battery degradation. The proposed machine learning-based system leverages real-time battery performance data, including metrics like voltage, current, temperature, and charge-discharge cycles, to train predictive models capable of estimating the Remaining Useful Life (RUL) of EV batteries. This approach significantly enhances accuracy by capturing complex patterns in battery degradation, enables real-time predictions for immediate insights, optimizes costs by minimizing unnecessary replacements and maximizing resource utilization, and promotes sustainability through efficient recycling and reduced battery waste.

Increasing the post-repair resource of the wheels attachment bolts of transport machinery

Abstract. Problem. The state of war in our country and a significant reduction in the production of new vehicles exacerbated the problem of increasing their operational resource due to repairs. Improving the quality and increasing the efficiency of transport vehicles involves, first of all, the fight against wear and tear, because the reason for their premature failure (from 75 to 90%) is significant wear and tear of parts. A significant number of parts of the main structural units of vehicles are exposed to cyclic loads, so it is quite reasonable to pay attention to the issue of increasing the fatigue strength of products. Considering the significant shortage and high cost of spare parts, an expedient and economically beneficial solution to these problems is the restoration and strengthening of the surface layers of products during repair The parts that mostly fail prematurely and require repair using rational methods of recovery include the bolts of fastening the wheels of buses - a very common vehicle that is intensively operated in very difficult conditions. The development of effective technological processes for the restoration of bolts with a simultaneous increase in the post-repair resource at the lowest costs is definitely an urgent issue, because it will prevent another possible premature failure in operation Goal. The purpose of the work is to restore and increase the post-repair resource of the bolts for fastening the disks of the rear wheels of the bus. Methodology. The subject of the study were the serial bolts for fastening the discs of the rear wheels of the bus made of 40X steel after quenching and tempering at 500-550º C with a trostite-bainite structure and a hardness of 35-37 НРС. For vibro-arc surfacing, electrode wire Нп-30ХГСА with a diameter of 1.2 mm was used. Food carbon dioxide was used as a protective gas, and a 5% solution of soda ash in water was used as an accelerating coolant. After surfacing, the surface was subjected to bombardment with low-energy (up to 3 keV) titanium ions in an argon environment at the Bulat - 3t installation. After the specified methods of bolt processing, the roughness and surface profile were evaluated, the microstructure was studied, and the mechanical properties were determined. The strength limit of the slotted part of the bolt was determined using special samples on the CD10 universal machine (made in Germany). Cyclic tests of welded samples were carried out according to the scheme "tension during rotation of the cantilever-loaded sample" on the UMP-02 machine. Tensile tests were performed according to standard methods. Originality. To increase the cyclic durability and wear resistance of bolts, a modern method of surface modification was used - ion bombardment with low-energy ions (without coating), which made it possible to strengthen the surface layer without losing plasticity. An increase in the resource was achieved due to a change in the state of the surface (obtaining ultrafine crystalline nano-sized grain, healing of surface stress concentrators), and a change in the mechanism of plastic deformation - from dislocation to rotational with grain-boundary sliding of ultra-fine grains. Practical value. The recommended mode of vibro-arc surfacing provides surface hardness for the possibility of further mechanical processing without additional thermal weakening, which increases the cost-effectiveness of the process of compensation of the worn surface layer. Modification of the surface by ion brombarbing after surfacing made it possible to increase the cyclic durability by 2 times, significantly increase the static strength without loss of plasticity, and increase the hardness to ensure wear resistance.

Assessment of atmospheric volatile organic compounds at two crude oil production plants in Southeastern Türkiye.

Ambient Volatile Organic Compounds (VOCs) were investigated to determine their characteristics, Ozone Formation Potentials (OFPs), and health risks in two crude oil production plants (Nusaybin and Egil plants) in southeastern Türkiye. Benzene, toluene, ethylbenzene, m + p xylene, o xylene, and 1,3,5-trimethylbenzene were measured at eight passive sampling points in each plant. Samples were analyzed using gas chromatography coupled with a flame ionization detector and a thermal desorption. The concentration of ranged from 5.03 to 88.43μg/m3 in the Nusaybin Plant and from 7.70 to 154.35μg/m3 in the Egil Plant. Toluene and xylenes were predominant in both plants. In the Nusaybin Plant, VOCs were mainly associated with crude oil production, while in the Egil Plant, they were associated with a combination of crude oil production and mobile vehicle activities. The OFP of was 297.47μg/m3 in the Nusaybin Plant, and 249.25μg/m3 in the Egil Plant. M + p xylene, toluene, and 1,3,5-trimethylbenzene together contributed 86% and 84% of the total OFP in the Nusaybin and Egil plants, respectively. Benzene exposure posed a possible cancer risk to oil workers in both plants. Non-cancer health risk was at a potential level in the Egil Plant but negligible in the Nusaybin Plant. This study is expected to enhance knowledge regarding the effects of crude oil production plants on air quality and workplace exposure.

Stability assessment of railway vehicles considering undefined nonlinearity in static force–velocity characteristics of hydraulic yaw dampers

Yaw dampers are usually tuned according to the nominal static force–velocity (F–V) characteristics specified by the vehicle manufacturer. However, in the low-speed region, the static F–V curve often varies significantly among damper suppliers due to a lack of standardised specifications. This variability underscores the necessity of accounting for nonlinearities in the analysis and understanding their relationship with the dynamic behaviour of yaw dampers and their impact on overall vehicle stability. To address these issues, we developed and validated a simplified physical damper model that incorporates these undefined nonlinearities through rig testing. Using this model, simulations were performed to investigate how these nonlinearities affect dynamic damper characteristics and vehicle stability. Our findings indicate that undefined nonlinearities in the low-speed region of the static F–V curve significantly influence the dynamic stiffness and damping of yaw dampers, particularly at small amplitudes and low frequencies. These effects have a pronounced impact on carbody stability in conditions with low wheel-rail conicity and significantly affect passenger’s comfort. The insights gained from this study offer valuable implications for the design, optimisation and standardisation of yaw dampers in high-speed trains.

IMPROVEMENT OF WAREHOUSE TECHNOLOGY IN INTERNATIONAL FREIGHT TRANSPORTATION

The article analyzes the existing methods of building cargo handling technologies in warehouses. The chosen topic is quite relevant, since the use of outdated warehouse infrastructure and the use of outdated mechanization equipment in most cases, the operation of warehousing facilities according to outdated transport and technological schemes in the processing of goods in warehouses; the absence or insufficient use of modern information systems for planning, organizing, controlling and accounting for warehouse operations; lead to significant financial losses. To address the issues related to the technological processing of goods in warehouses, the author proposes a methodology for developing and implementing a technology for determining the rational number of new highly maneuverable and energy-efficient machines. Modern requirements for warehouse operations necessitate the development and implementation of new innovative vehicles that will increase the productivity of warehouse operations by increasing the level of maneuverability and productivity of such vehicles. As a result of the calculations, it was determined that the application of the proposed approach to determining the rational number of new highly maneuverable and energy-efficient machines will reduce the cost of technological cargo handling. When handling the maximum amount of cargo arriving at the warehouse, the total cost of handling such cargo using the proposed mechanisms will be less than when using existing forklifts. When implementing the developed methodology for determining the rational number of mechanisms for performing loading and unloading operations during the technological processing of goods in warehouses, it is possible to obtain a significant economic effect. Under certain conditions of technological handling of goods in warehouses, it is advisable to use simulation modeling of the processes included in the technological schemes of cargo handling. In this case, it is necessary to take into account the external influence of various factors that can lead to significant disruptions in the warehouse.

The development of Iran's industry during the period of sanctions

Subject. This article discusses the impact of international sanctions on Iran's economic policy. Objectives. The article aims to analyze the development of manufacturing industries in Iran in the context of sanctions in general, and the automotive and aviation industries in particular. Methods. For the study, we used the mathematical research methods. Results. Based on the analysis, the article shows that Iran's manufacturing industries have developed and keep on developing under sanctions due to cooperation with other countries, primarily with China, the import of the necessary components through third countries, and the creation of own models of machinery and equipment. Despite all the restrictions, the Iranian automotive industry has been able to achieve a high level of localization of components, and particular attention is paid to the production of unmanned aerial vehicles. Conclusions. Iran has been able to get adapted to the sanctions imposed on it for its product diversifying markets, expanding cooperation with third countries and striving for self-sufficiency in production. It should be noted that the sanctions were introduced gradually. The experience of developing manufacturing industries in Iran during the period of sanctions can be used by other countries.

Solving the combined flexible job shop scheduling and vehicle routing problem with stochastic features

ABSTRACT Today’s competitive market conditions forces companies to implement strategies for the integration of production and transportation activities, but this is studied little in the literature. This paper considers the combined production and transportation problem in which the production system is defined as a flexible jobshop (FJS) and the transportation stage is modelled as a vehicle routing problem (VRP). Stochastic production processing times and vehicle travel times are considered. A simheuristic solution procedure is proposed, as a class of simulation-optimisation approach, based on Ant Colony Optimisation (production stage) and an iterative local search (transportation stage). Randomised data sets are used to evaluate the performance of the proposed solution procedure, with metrics such as total production time and delivery time demonstrating its effectiveness. Experimental outputs show the impact of considering stochasticity of these two parameters for better decision-making. Compared to existing methods, our approach offers significant improvements in efficiency and reliability.

Features of Indonesia’s Low-Carbon Development Strategy

The purpose of the article is to identify trends and features of the development of a low-carbon economy and climate control tools in Indonesia using methods of content analysis, quantitative and comparative assessment. Climate goals declared for the period up to 2030 and 2050 are analyzed and there has been a rise in climate ambitions, based largely on measures to decarbonise the land and forestry sector. The peculiarity of Indonesia's climate goals is that they are defined relative to a business-as-usual scenario, which assumes the current rate of growth in greenhouse gas emissions and are calculated subject to the provision of international financial assistance. The long-term strategy for low-carbon development until 2050 is considered and government priorities in the field of climate regulation are identified. While forced to maintain coal generation as its long-term energy backbone, Indonesia is seeking to pursue other avenues: introducing carbon pricing, incentivizing renewable energy, increasing production of electric vehicles, and developing and deploying carbon capture technology. By providing state support to priority areas, Indonesia actively takes advantage of the opportunities provided by international financial organizations to finance climate projects. It is concluded that the long-term low-carbon development strategy and associated climate goals in terms of greenhouse gas emissions and the time frame for achieving carbon neutrality are quite moderate, since they are based on a comparison with the business-as-usual scenario. With this approach to strategic planning, it will be possible to achieve the set goals by implementing measures only in the land and forestry sector, while the volume of greenhouse gas emissions in other sectors may not decrease, but increase in absolute terms. This approach is explained by national interests and the desire to preserve coal generation in the energy sector.

Dimensional Evaluation of Additively Manufactured Parts for Autonomous Vehicles

The growing use of drones in civilian and military applications is motivated mainly by reduced costs. Drones, along with autonomous vehicles, require lightweight structures and high dimensional accuracy to improve autonomy and spatial orientation. Additive Manufacturing (AM) enables the production of lightweight parts by controlling internal fill percentages and optimizing the density. However, there is limited research into how the type and percentage of infill affects dimensional tolerance. This study aims to assess the impact of these factors on 3D-printed parts, using low-cost FFF 3D printers with Polylactic Acid (PLA) and Acrylonitrile Butadiene Styrene (ABS) filaments. Overall, the results were satisfactory and met the required tolerances, confirming the feasibility of using parts produced by low-cost 3D printers and commonly available materials in the mass production of drones and autonomous vehicles.

МОДЕЛЬ УПРАВЛІННЯ ЯКІСТЮ ТЕХНІЧНОЇ ПІДГОТОВКИ ВИГОТОВЛЕННЯ КОРПУСІВ БПЛА

Nowadays, the production of unmanned aerial vehicles (UAVs) outside of serial production is an urgent task. There is a need for the manufacture of such devices of various schemes, sizes and intended purpose. Aircraft-type UAVs (monoplanes and biplanes) are more difficult to manufacture. As a rule, they are single-use devices. Therefore, such devices should have a simple design, be light enough, have minimal radio visibility and a number of other properties that are necessary for conventional flying apparatus. Composites (glass and carbon plastics) are materials that largely meet the specified requirements. But for these materials, it is necessary to use special structural and manufacturing solutions (SMS) during the technical preparation of their production (TPP) (production of aerodynamic surfaces, assembly and joining of parts, aggregates into a structure). Quite a lot of such solutions are known, but their optimal selection and combination of individual SMS in the UAV depends significantly on the purpose of the UAV, the volume of production, production conditions and, in general, on the production goals.The purpose of this work is to develop a mathematical model for quality management of technical preparation for the production of UAVs. It is the quality of the technical preparation of the production that determines the quality of the manufactured products and the effect of the production itself.The work gives a general diagram of UAV manufacturing processes. The inextricable connection between the design and technological parts of technical training was noted. The multi-iteration process of developing optimal production processes, which depend on its various goals, is shown. The systematicity, compactness, and reasonableness of the solutions are determined by taking into account many properties of technical processes and the conditions of their implementation. The consideration of possibilities in computer-aided design is sufficiently substantiated. For its implementation, a complex model of quality management of technical training is required. The qualitative approach to model synthesis meets the conditions of complexity and reasonableness.As an example of multi-variability, the SMS of the manufacture of the wing (bearing surfaces) and their connection with the fuselage is considered.The original feature of the proposed mat model is the use as a control parameter of the weighting factor of one or another property of the SMS, which depends on the set goal.The mechanism of distortion of given aerodynamic shapes of bearing surfaces, which are made of polymer composites, when they are supported by various structural elements (spars, stringer frames, fittings) is described. Such residual deformations lead to deterioration of aerodynamic quality and strength.The scientific novelty of the work consists in the synthesis of a mat model of quality management of technical preparation for the manufacture of UAVs. The practical value of the work is determined by the given number of examples of SMS variants of different levels.

In situ torque transmissibility frequency response function measurements of a centrifugal pendulum vibration absorber in a torque converter clutch damper

This investigation details torsional testing and characterization of torque converter clutch (TCC) damper variants containing centrifugal pendulum absorbers (CPAs) utilized in light duty production vehicles. Data collected on a torque converter dynamometer test stand was used to correlate a nonlinear model of the combination TCC damper and CPA when locked with zero relative slip speed. The range of test torques and speeds are related to when driveline, chassis and body noise and vibration concerns are high and the damper-CPA combination are required to provide maximum isolation. To facilitate model correlation efforts, modified configurations of the same torque converter design were procured, enabling separation of damping effects from the CPA and damper springs. Under load, the locked TCC was torsionally excited to acquire torque transmissibility frequency response functions (TTFRFs). The anti-resonance of the CPA was measured, and the viscous damping coefficient estimated. A manual tuning and modified half-power bandwidth method were used to estimate the equivalent viscous damping of the CPA. Additional test cases included torsional excitation amplitude and oil temperature to ascertain differences in CPA response and tuning order. The objective of the investigation is to demonstrate the influence of damper spring and CPA integration, extraction of CPA damping from actual hardware and the utility of including representative damping in model-based design of future damper-CPA assemblies.