Car Fleet Research Articles

A comparative analysis of car fleet efficiency evolution in Europe and Australia insights on policy influence

Regulators worldwide introduce measures to improve energy consumption and reduce greenhouse emissions of road vehicles. The present study focuses on the impacts of passenger car carbon dioxide (CO2) and fuel efficiency measures, attempting to evaluate their effectiveness using vehicle and fleet modelling. To obtain a robust counterfactual result, two regions are compared as a case study: the European Union (EU), where CO2 emissions have been regulated for over fifteen years, and Australia, a region that recently introduced such a policy element. The average difference in the certified CO2 emissions of new cars registered in the two regions increased from 50g/km in 2018 to 60g/km in 2021 due to accelerated electrification in the EU. To demonstrate the importance of mandatory targets, a sensitivity analysis of the 2020 EU registrations showed that lower by one-third sales of zero and low-emission vehicles (Z-L-EVs) would have resulted in seven out of ten manufacturer pools failing to meet the 2020 target of 95g/km. The simulation framework was validated against certified values of 2021 registrations and was subsequently used to calculate real-world fleet performance to quantify the actual emissions savings. The real-world CO2 emissions in the registered fleets for 2021 were estimated to be 143g/km and 204g/km, for the EU and Australia, respectively. With these results as a reference, the share of ZEVs required to meet the targets set in both regions is calculated: 51% of the new registrations in 2030 in the EU for achieving 49.5g/km, and 60% in Australia for recently set target of 58g/km for 2029. The respective calculated average fleet-wide real-world tailpipe CO2 emissions were estimated to be 66g/km (EU) and 77g/km (Australia). As a last step, the study discusses the application of similar tools and analysis in the design of future policies.

The Circular Industrial Transformation System (CITS) model - Assessing the life cycle impacts of climate and circularity strategies

The Circular Industrial Transformation System (CITS) model - Assessing the life cycle impacts of climate and circularity strategies

Distributed intelligence in industrial and automotive cyber-physical systems: a review.

Cyber-physical systems (CPSs) are evolving from individual systems to collectives of systems that collaborate to achieve highly complex goals, realizing a cyber-physical system of systems (CPSoSs) approach. They are heterogeneous systems comprising various autonomous CPSs, each with unique performance capabilities, priorities, and pursued goals. In practice, there are significant challenges in the applicability and usability of CPSoSs that need to be addressed. The decentralization of CPSoSs assigns tasks to individual CPSs within the system of systems. All CPSs should harmonically pursue system-based achievements and collaborate to make system-of-system-based decisions and implement the CPSoS functionality. The automotive domain is transitioning to the system of systems approach, aiming to provide a series of emergent functionalities like traffic management, collaborative car fleet management, or large-scale automotive adaptation to the physical environment, thus providing significant environmental benefits and achieving significant societal impact. Similarly, large infrastructure domains are evolving into global, highly integrated cyber-physical systems of systems, covering all parts of the value chain. This survey provides a comprehensive review of current best practices in connected cyber-physical systems and investigates a dual-layer architecture entailing perception and behavioral components. The presented perception layer entails object detection, cooperative scene analysis, cooperative localization and path planning, and human-centric perception. The behavioral layer focuses on human-in-the-loop (HITL)-centric decision making and control, where the output of the perception layer assists the human operator in making decisions while monitoring the operator's state. Finally, an extended overview of digital twin (DT) paradigms is provided so as to simulate, realize, and optimize large-scale CPSoS ecosystems.

THE STUDY OF THE TECHNICAL CONDITION OF GONDOLA CARS

The article presents the results of the analysis of the technical condition of gondola cars owned by the transport operator BGS rail. The composition of the model range of the car fleet was analysed. It is shown that 14 % of gondola cars produced by Uralvagonzavod have an average service life of over thirty years and have exhausted their service life. Gondola cars of models 12-757 and 12-753 of Kryukov Carriage Works have also exhausted their service life. A positive factor is the presence of innovative cars model 12-7023 produced by KVSZ and 12-4106 model produced by PJSC Dneprovagonmash in the car fleet. Their average age is 6.5 years.An analysis of the main causes of failures that caused the car to uncouple from the train along the route was carried out. In the first place are damage to body elements. This is followed by failures of automatic brakes and wheel sets.Among the damage to gondola car bodies, the first place is taken by malfunctions of the locks on the unloading hatch covers, followed by cracks and breaks in the upper and vertical sheets of the frame cross beams. Broken weld seams of braces and broken linings also pose a serious danger.Failures of auto brakes are caused by loosening of air duct pipes, brake equipment and welded shoes. The main causes of damage to wheel pairs are unacceptable wear of the flange. Among axle box assemblies, the vast majority of failures are caused by excessive heating of the bearings.Failures of automatic coupling equipment are most often caused by fractures of the centering beam and breaks (cracks) of the pendulum suspension. Cracks and other malfunctions of the automatic coupling body are also observed.The bogies mostly have broken springs and mismatched sliding clearances. Also, a quarter of the uncoupled bogies have expired service life of their elements. The average recovery time for gondola cars was analyzed. Due to malfunctions of axlebox units, cars are under repair for more than 15 days, due to failures of wheel pairs - 11.55 days. The least time is spent on auto brakes – 4.2 days.An analysis of the damage to the bodies of various gondola cars models showed that gondola cars of models 12-9745 and 12-9790 are in the worst technical condition. The least susceptible to damage are the «innovative» gondola cars of models 12-7023 and 12-4106.

THE NOTION OF SEQUENTIALITY IN LANGUAGE: AN INVESTIGATION IN COGNITIVE SEMANTICS

AbstractThis research aims to clarify the concept of sequentiality in language: the case in which a number of things occur one after the other, as seen in phrases like a queue of customers, a strand of programs and a fleet of cars. Utilizing Langacker's theory of Cognitive Semantics, the study seeks to substantiate two claims. The first is that the meaning of a linguistic expression is understood in terms of the domain in which it is embedded. The second is that the meaning of a linguistic expression is the outcome of the specific construal imposed on its content. The paper proposes that the choice of a sequential phrase is influenced by how the speaker perceives and describe a situation. The study intends to demonstrate that each sequential phrase carries a unique meaning that sets it apart from others. When two or more sequential phrases modify a noun, they indicate semantic contrast, with each phrase offering a different perspective. The findings show that sequential phrases have distinct functions and are distinguishable in their usage through examples provided.

Energy transition in Portugal: The harnessing of solar photovoltaics in electric mobility and its impact on the carbon footprint

Energy transition in Portugal: The harnessing of solar photovoltaics in electric mobility and its impact on the carbon footprint

Contribution to pollution by different types of vehicles based on age and number

This study assessed the smoke, hydrocarbon (HC), and carbon monoxide (CO) emissions from a range of age groups and car types. The results show a distinct trend of rising emissions with vehicle age, with older cars having the greatest emission levels. Older cars (20+ years) had emissions of CO (18.83 times higher), HC (5.81 times higher), and smoke (3.97 times higher) than newer cars (0–5 years), suggesting that older cars play a major role in air pollution. Similar to cars, motorbikes showed a significant increase in emissions. In the group of people aged 5 to 10, CO emissions increased from 0.63 times to 7.00 times, while HC emissions increased from 0.72 times to 6.20 times. Both trucks and buses showed similar trends: for vehicles older than 20 years, CO emissions peaked at 3.28 times and HC at 6.20 times, while for buses, CO emissions peaked at 1.55 times and smoke levels peaked at 5.50 times. The CO emissions of autorickshaws, which are often utilized in metropolitan areas, also increased significantly with age. For example, the CO emissions of autorickshaws increased from 0.97 times in the 5–10 year group to 13.85 times in cars over 20 years old. These results illustrate the negative effects that older cars have on the environment and the necessity of stricter emissions standards for fleets of aging cars.

VARIABLE ASSESSMENT OF THE TRANSPORT AND LOGISTICS SCHEME FOR THE DISTRIBUTION OF GOODS TO THE TRADE NETWORK

The distribution of goods to the trade network is a complex process that requires a careful approach to determining the hierarchical structure of the interaction of participants in the logistics chain and planning their activities. An essential element of this process is choosing the configuration of the transport and logistics scheme, which ensures efficient and timely delivery of goods to the trade network. In this study, we propose to carry out a variable assessment of the efficiency of the distribution of goods according to basic schemes on the ground of taking into account a set of factors, such as the distance of transportation, volume of cargo, delivery terms, specific costs for transportation and storage of freight, the impact of changes in the speed of movement and the time of cargo operations. It makes it possible to present the choice of a rational transport and logistics scheme in the form of an optimisation process to make it more flexible and adaptable to the changing conditions that characterise the current distribution of goods. The article aims to establish a rational structure for determining the efficiency of the delivery of goods to the trade network based on evaluating a sensible version of the transport and logistics scheme, which ensures the conditions for implementing technological operations in time. The methodological basis for establishing a rational version of the transport and logistics scheme is a developed structural model of the influence of input parameters on the total costs and timeliness of delivery of a batch of goods to the trade network. Such a research model describes the functional relationship between incoming information flows about the volumes of orders for the delivery of goods, the nature of changes in the parameters of cars in motion and under loading-unloading, information about the structure of the available car fleet, and the characteristics of the communication network and the controlling influences represented by the choice of a rational total of trunk and delivery routes. Designating a logical sequence of communication between these flows enables determining the value of the components of the efficiency criterion of the transport and logistics delivery system. We established that the transport and logistics scheme of delivery is the basis for the development of transportation routes and the organisation of the functioning of warehouse distribution complexes. The developed structure for evaluating the efficiency of the delivery of goods to the trade network allows for determining the core conditions of activity of the logistics chain participants and specifying a set of technical, operational, and economic indicators of their work. Accounting for the time parameters of the transport and logistics chain enables taking into account the influence of fluctuations in the high-speed mode of movement and idle time at loading and unloading points. The developed models for estimating the time parameters of cargo delivery facilitate efficient planning of the transportation routes and determine the rational time for delivery of each consignment. All local models work in a complex with the general structure of evaluating the efficiency of goods delivery and ensuring a more efficient and transparent management of logistics processes. Their use allows logistics companies to reduce delivery costs, improve the quality of customer service, and increase the competitiveness of the trading network in the market. Keywords: delivery, product, trade network, delivery chain, logistics system.

Changes in Car Fleet Management as a Result of the COVID-19 Pandemic - The Case of Polish Companies

Changes in Car Fleet Management as a Result of the COVID-19 Pandemic - The Case of Polish Companies

The impact of demand-side strategies to enable a more circular economy in private car mobility

The impact of demand-side strategies to enable a more circular economy in private car mobility

Bearing Steel Structures for Installation of Railway Strain Gauge Scales

Purpose. The main purpose of the publication is to compare the main technical and economic indicators of the two proposed structural variants of the support system for railway strain gauge scales for four-axle wide gauge railcars. This is due to the need to reconstruct and modernize the fixed assets of an industrial enterprise, in particular, to overhaul and replace old railway scales with modern electronic strain gauge scales. Also, the purpose of the work is related to the need to expand the range of railway cars for which the possibility of weighing is provided, including transport units of the foreign car fleet. Methodology. To achieve this goal, we analyzed the modern types of railroad cars for freight transportation, determined the main components of strain gauge scales for weighing the main types of cars, and developed a special support system to support the scale platform. The support system is provided in two design variants - with one spatial support frame and two separate flat support frames. Using the domestic design and computing complex SCAD, we built finite element models for both proposed design options. Based on the analysis of their stress-strain state, rational cross-sections were selected for each structural element, and the total mass was determined. Findings. A comparative analysis of the two developed structural solutions for the support system for modern railway strain gauges has revealed that the variant with two separate bearing frames has a lower weight by about 40 % compared to the variant with one spatial bearing frame. However, the manufacturability of its production is somewhat lower, since it involves 10 structural elements compared to 7 for variant No. 1. Originality. The numerical analysis made it possible to theoretically substantiate a more rational and efficient design solution for the support system for modern railway strain gauge scales. Practical value. A constructive variant of the steel support system has been developed and proposed for practical implementation, which is the most effective in terms of its technical and economic indicators for the existing conditions of an existing industrial enterprise. The developed design option was also coordinated with the project of major reconstruction of the building for weighing railroad cars.

Traffic planning in modern large cities Paris and Istanbul

The enhancement of flexibility, energy efficiency, and environmental friendliness constitutes a widely acknowledged trend in the development of urban infrastructure. The proliferation of various types of transportation vehicles exacerbates the complexity of traffic regulation. Intelligent transportation systems, leveraging real-time traffic status prediction technologies, such as velocity estimation, emerge as viable solutions for the efficacious management and control of urban road networks. The objective of this project is to address the complex task of increasing accuracy in predicting traffic conditions on a big scale using deep learning techniques. To accomplish the objective of the study, the historical traffic data of Paris and Istanbul within a certain timeframe were used, considering the impact of variables such as speed, traffic volume, and direction. Specifically, traffic movie clips based on 2 years of real-world data for the two cities were utilized. The movies were generated with HERE data derived from over 100 billion GPS (Global Positioning System) probe points collected from a substantial fleet of automobiles. The model presented by us, unlike the majority of previous ones, takes into account the cumulative impact of speed, flow, and direction. The developed model showed better results compared to the well-known models, in particular, in comparison with the SR-ResNet model. The pixel-wise MAE (mean absolute error) values for Paris and Istanbul were 4.299 and 3.884 respectively, compared to 4.551 and 3.993 for SR-ResNET. Thus, the created model demonstrated the possibilities for further enhancing the accuracy and efficacy of intelligent transportation systems, particularly in large urban centres, thereby facilitating heightened safety, energy efficiency, and convenience for road users. The obtained results will be useful for local policymakers responsible for infrastructure development planning, as well as for specialists and researchers in the field. Future research should investigate how to incorporate more sources of information, in particular previous information from physical traffic flow models, information about weather conditions, etc. into the deep learning framework, as well as further increasing of the throughput capacity and reducing processing time.

Compact Pollution Control and Sound Indicator Device

Abstract: The increasing urbanisation of cities globally has intensified worries about car pollution, leading to substantial environmental damage and public health risks. Current Pollution Under Control (PUC) systems, which primarily focus on reducing exhaust emissions, often encounter usability problems and neglect the issue of noise pollution. This study presents a new and innovative approach called the Compact Pollution Control and Sound Indicator Device (CPCSID), which aims to overcome these limitations. The project includes state-of-the-art sensors capable of discriminating and measuring several exhaust gases generated by cars, including nitrogen oxides (NOx), carbon monoxide (CO), and carbon dioxide (CO2). Additionally, it contains an integrated microphone to assess engine-generated noise levels. The LCD panel presents real-time data of pollution and noise, providing consumers with practical insights into the environmental effects of their car. In addition, our invention is integrated with a GSM module, which allows it to send SMS notifications to car owners. These warnings aim to promote environmentally aware behaviour and enable quick responses to reduce pollution. The small size and easy-to-use design make it suited for both individual car owners and fleet managers, providing a complete solution for reducing automobile pollution in urban areas.

Bitumen-Biopolymer Materials Modified with Polylactic Acid with Improved Physical and Chemical Properties

With the continuous expansion of the global automobile fleet, there is an escalating demand to enhance and maintain current road infrastructure. Given the information provided, there will be a growing demand for bitumen, a key raw material used in the manufacturing of asphalt. Bitumen may account for up to 60% of the total usage in asphalt production. This study aims to determine the effect of different content of polylactic acid (PLA) on the change in the chemical and physical properties of biopolymer bitumen during its modification. This study was carried out by using a sample of petroleum road bitumen from CASPI BITUM (Kazakhstan) and a sample of PLA from Zhejiang Hisun (China). As a part of the research, the change of quality indicators of biopolymer bitumen when adding 4%–10% of PLA to it has been established. The results showed that the values of the average molecular weight and average molar mass increased with increasing the content of PLA in biopolymer bitumen. In particular, when the PLA content in biopolymer bitumen increased up to 10%, the average molecular weight of the biopolymer bitumen increased from 1,263 to 2,759 Mw and the average molar mass increased from 1,215 to 1,395 Mn. It was shown that increasing the PLA content in biopolymer bitumen from 0% to 10% leads to an increase in the softening temperature from 47 to 70°C or ∼ 49%. It was found that all examined samples of biopolymer bitumen are characterized by increased plasticity at 25°C (>100 cm). It has been established that the addition of 8% PLA to bitumen allows one to obtain a biopolymer bitumen of optimal quality. The results obtained can be used to produce road biopolymer bitumen.

Simulating the effects of tax exemptions for plug-in electric vehicles in Norway

For many years Norway has been in the forefront of promoting electromobility. Today, Norway has the world’s highest per capita fleet of plug-in electric cars. In 2021, 1.6% of the cars in the EU fleet were plug-in electric vehicles, whereas their share was 21% in Norway. Part of the successful market take-up rate is due to wide-ranging tax exemptions. Increasing plug-in electric vehicles numbers causes tax revenue losses, making exemptions unsustainable. Norway has the ambitious goal that from 2025, all newly registered cars shall be zero-emission vehicles. Keeping tax exemptions in place might be crucial for this goal. The objective of this paper is to provide information to solve this dilemma. Tax exemption reduction and abolition paths which offer a compromise between minimal effects on the development of zero-emission vehicles and tax revenues have been identified. An updated and re-calibrated version of the stock-flow-model SERAPIS was used to simulate and assess different scenarios. Results show that a controlled tax phase-in allows Norway to reach its environmental targets of 100% zero emission vehicles by 2025 and a 55% decrease of CO2-emissions in 2030 relative to 2005 while simultaneously increasing public revenues significantly.

Trends, main economic determinants of the e-mobility in the EU: Additional evidence and verification

The adoption of e-mobility in the countries of the European Union shows significant differences in terms of dynamics of electric car sales and in terms of differences in the share of electric cars in the total fleet of passenger cars in individual Member states. Despite the common European policy of transition to less emission-intensive car drives, the economic performance of countries, as well as other determinants, turn out to be the key drivers of differences in the sales and shares of electric cars on the car fleet within individual countries. In light of these findings, the paper contributes to the existing discussion and knowledge with additional recent findings and how intensive main consensual factors cause differences in the recent electric cars market shares in the EU countries.

ON THE ISSUE OF DETERMINING THE PRODUCTION COST OF THE CAPITAL RENEWAL OF PASSENGER CARS

In recent years, the inventory of passenger cars has decreased significantly due to the exclusion from service of the ones that have already exhausted their service life. The wear and tear of the passenger rolling stock of Ukrzaliznytsia JSC is approaching 90%. Repair and maintenance costs for outdated railcars account for over half of the industry’s expenses. In conditions of an acute shortage of newly built cars, practically the only way to maintain the operability of the car fleet is to overhaul passenger cars that have exhausted their service life. At the same time, based on the results of operations in different regions, the railway cars have different technical conditions. Also, different car repair enterprises use differing methods for calculating the cost of repairs. It leads to a significant scatter of calculation results. The article is devoted to the issue of creating a generalised methodological approach to determining the production cost of passenger cars overhaul. We have classified production costs and determined which expenses relate to the direct costs of car repair production, the auxiliary production costs, and general production costs. Next, we formulated the components of each of these groups. The article considers the main aspects influencing the formation of costs, particularly labour costs and social contributions, material costs, fuel, electricity, repairs, and equipment depreciation. It also takes into account the cost of return expenses. The proposed scientific approach allows accounting for the actual service life and level of wear of the passenger car, its type, and design features. We carried out an analysis of the factors affecting the production cost of repairing passenger cars. It makes it possible to determine rational technical and organisational solutions to reduce the cost of overhauling passenger cars that have exhausted their service life. The stated provisions have a practical orientation and can be used at the car repair enterprises of the Passenger Company branch of JSC Ukrzaliznytsia. Keywords: passenger car, repair, resource, wear and tear, production cost, expenses.

Undoing the lock-in of suburban sprawl: Towards an integrated modelling of materials and emissions in buildings and vehicles

Undoing the lock-in of suburban sprawl: Towards an integrated modelling of materials and emissions in buildings and vehicles

Методика определения потерь участковой скорости движения грузовых поездов в границах железной дороги

Purpose: to develop a methodology for estimating the total losses of the local speed of freight trains, which, unlike existing methods based on calculating losses caused by the influence of individual operational factors, will be based on the use of statistical data, and take into account the entire range of operational factors that influence the implementation of the indicator under consideration. Methods: formation of a statistical database of railway operational parameters and conducting research on its basis using the tools of probability theory and mathematical statistics: assessing the distribution of the quantities under consideration, correlation and regression analysis. Results: it was established that 75 % of the variability in the local speed of freight trains is explained by changes in the size of the operating fleet of freight cars. Based on this, a methodology has been developed for estimating losses in the local speed of freight trains through the size of the working fleet of freight cars on the railway. A graphical and analytical method for determining these losses is proposed. Practical significance: it is shown that the developed methodology, in contrast to existing ones, makes it possible to more accurately estimate the loss of local speed of freight trains. Its use makes it possible to plan and analyze the implementation of the local speed of freight trains, taking into account the evolving operational work on the railway.

Exploring the Relationship Between CO2 Emissions and Fuel Consumption in Road Transport: Empirical Evidence from Chad

Over the period 2008-2019, this study examines the linear impact of petroleum product (PP) consumption in Chad, PP prices, the vehicle fleet and urbanisation on CO2 emissions on the one hand, and on the other, it determines the causal links that exist between the various variables studied. This study opts for the augmented Dickey-Fuller and Phillips-Perron tests to verify the stationarity of the variables. The ARDL model is then estimated and diagnostic tests are performed to confirm the validity of the model. To confirm the existence of long-term relationships, the bounds test was applied. Finally, the Toda-Yamamoto causality test was used to capture the influences present between the series under study. The main results show that, in the long term, a 1% increase in gasoline consumption would lead to a 1.03% increase in CO2 emissions and the linear impact of diesel consumption is positive and insignificant on CO2 emissions. In the short term, gasoline and diesel consumption have a positive and insignificant impact on CO2 emissions. In terms of causality, there is a unidirectional causality from gasoline consumption to CO2 emissions and a bidirectional causality between CO2 emissions and diesel consumption. This study is the first to simultaneously link CO2 emissions, PP consumption, PP prices, the vehicle fleet and urbanisation in general, and particularly in the case of Chad. It therefore adds to the literature on the simultaneous relationship between CO2 emissions, PP consumption, the car fleet and urbanisation in a global and restricted context. This study could guide Chadian oil pollution management decision-makers in adopting policies related to the effects of PP consumption in the road transport sector.