Impact Of Vehicles Research Articles

Safety barriers under changing operating conditions–An analysis of impact parameters in Germany

Vehicle restraint systems and especially the impact of a collision on such are subject to various influencing variables. These systems are tested and approved through vehicle impact tests to ensure that safety standards are met as well as to ensure comparability amongst the systems. However, differences in the objectives of the standard DIN EN 1317 and the behaviour in practice have become apparent.There is the standard DIN EN 1317 which defines the impact tests on testing grounds. Nevertheless, there are a number of influencing parameters such as developments in the vehicle fleet over the last years, available safety barriers, including their construction types and the impact itself. Previous research indicates that there could be a gap between these parameters.This research uses an empirical analysis based on chiefly quantitative data sources to evaluate the differences between these parameters. It leads to a partial divergence between static requirements of the standard and the actual road traffic conditions. Additionaly, the differences are developed within a vulnerability analysis and for the purpose of comparison, the advantages as well as the disadvantages of the standardized impact tests are discussed in this paper.As a result, a parameter based suggestion for a reevaluation of impact tests for safety barriers, according to the standard DIN EN 1317, is advisable due to the changing road traffic on the current stock and new barrier systems to be built. This research strives to illuminate the trend for new investigation methods such as the finite element method (FEM) simulation. It gives an outlook to further research needs in safety barriers, principally in the observation of the future development of the impact parameters. At the same time, impulses and potential for improvement can be identified for the future documentation of vehicle impacts on these barriers.

ANALYSIS OF TYPES OF VEHICLE POWER PLANTS: ADVANTAGES AND DISADVANTAGES

This paper analyzes the advantages and disadvantages of vehicle power plants, examines the development and modern types of hybrid power plants used in transport. An analysis of carbon dioxide (CO2) emissions into the atmosphere from vehicles equipped with different types of powertrains, including internal combustion engines (ICE), hybrid drives, and electric motors, was performed. Studies have been conducted of emissions that occur during the operation of vehicles, as well as emissions associated with the production of high-voltage batteries for electric vehicles and the production of electricity required for their charging. It was concluded that electric vehicles, despite their popularity as environmentally friendly vehicles, can have a significant impact on the environment. This is due to high CO2 emissions during the production of batteries, which are a key component of electric vehicles. The production of these batteries requires significant energy costs and the use of various materials, the extraction and processing of which also lead to greenhouse gas emissions. In addition, the environmental impact of electric vehicles largely depends on the sources of electricity used to charge them. When electricity is generated from fossil fuels such as coal or natural gas, overall CO2 emissions can be significantly higher, reducing the environmental advantage of electric vehicles over internal combustion engines. On the other hand, the use of renewable energy sources, such as solar or wind energy, to charge electric vehicles significantly reduces CO2 emissions into the atmosphere. The work also considers hybrid vehicles that combine an internal combustion engine and an electric motor. Such cars usually have lower CO2 emissions during operation compared to traditional diesel vehicles, but their environmental impact also depends on the production and disposal of batteries. To make informed decisions about the choice of powertrain and the development of transport infrastructure, all aspects must be taken into account, including the production of vehicles, their operation and disposal. It is also important to develop technologies to reduce emissions and increase energy efficiency at all stages of a vehicle's life cycle. The work concluded that to reduce the overall impact of vehicles on the environment, it is necessary not only to develop electric vehicles, but also to combine the advantages of internal combustion engines and electric motors (develop a hybrid drive), improve battery production technologies, expand the use of renewable energy sources, and implement other measures to reduce CO2 emissions.

Carbon reduction effects of electric delivery vehicle adoption in Chinese cities: Gradient pattern and scenario analysis

China's carbon peak and neutrality targets pose major challenges for the transportation sector due to its significant contribution to carbon emissions. The analysis of the penetration process and impact of electric delivery vehicles (EDVs) in the urban delivery industry (UDI) is relatively poor compared with electric passenger vehicles. This study conducts a scenario analysis of the electrification process and carbon impact of delivery vehicles (DVs) in Chinese cities based on current data and policies. In the baseline scenario, the stock of urban DVs is predicted to reach 22.4 million in 2035, while the stock of EDVs will reach 7.8 million, representing 35 % of the total. Carbon emissions from DVs will decline from a peak of 120.5 Mt in 2022 to 101.4 Mt in 2035 due to the penetration of EDVs. The high electrification rate (HER) scenario will result in an additional 10 Mt of carbon emissions reduction in 2035 as 45 % of DVs are electric. Furthermore, the impact of electrification on carbon emissions shows a spatial gradient due to city size and local policies. With a better understanding of EDV adoption and energy-related carbon emissions in Chinese cities, suggestions are proposed to promote low-carbon transition of UDI in different types of cities.

Spike load smoothing strategy considering behavioral decision under vehicle-road-network convergence

To reduce the impact of large-scale electric vehicles on traffic and electric load peaks, we propose a "vehicle-road-network" integration strategy that takes into account behavioral decisions. To reduce the impact of large-scale electric vehicles on traffic and electric load, we propose a peak load suppression strategy that takes into account behavioral decisions under "vehicle-road-network" integration. Firstly, a "vehicle-road-network" fusion model is constructed based on the large-scale access of EVs; then, a load model is built considering the large-scale access of EVs; finally, based on the third-generation foreground theory, the behavioral decision of EV users is analyzed based on the operation state of the fusion system, and a decision model is built by the foreground value to minimize the operation cost. The spike load smoothing strategy scheme is established with minimum operation cost. By using the fusion of Sioux Falls urban road network system and IEEE33 node grid system as the simulation example, the simulation results show that the proposed peak load smoothing strategy can coordinate the distribution of charging load and relieve traffic pressure during peak load hours, and reduce the travel and charging costs of EV users.

Research on the Social Development of New Energy Vehicles based on XGBoost-SHAP and GA-biLSTM Models

China deeply promotes the implementation of new energy gas vehicle national strategy, new energy automobile industry continues to develop healthily, and gradually become an important force to promote the transformation and upgrading of the global automobile industry. In order to understand the impact of various domestic factors on the development of new energy vehicles, this paper firstly adopts the Delphi method to establish the index system of new energy vehicle development, and establishes the XGBoost-SHAP evaluation model to explore the development of China's new energy vehicles; secondly, it adopts the GA-biLSTM prediction model to forecast the time sequence of the comprehensive development indexes of new energy vehicle industry. Finally, through the social impact analysis of new energy vehicles, a simulation model is established to explore the impact of new energy vehicles on the ecological environment.

The impact of electric vehicles and photovoltaic energy integration on distribution network

The impact of electric vehicles and photovoltaic energy integration on distribution network

Impact Resistance Performance and Damage Characteristics of Mortise-and-Tenon Joint Prefabricated Bridge Piers

The mortise-and-tenon joint prefabricated connection combines the assembly form of mortise-and-tenon joints and cast-in-place wet joints. It achieves reliable joint connections through small joint depths and lap-spliced reinforcement lengths. To study the impact resistance and damage characteristics of the assembled pier, a nonlinear finite element analysis was performed on the assembled and monolithic pier model piers to study the effects of mortise-and-tenon joint depths, lap reinforcement, and grout on the response of the piers to vehicle impact. The results showed that, after impact, the damage to the prefabricated pier was similar to that of the monolithic one. The failure mode involved opening of the seam at the impact face-pier bottom junction and localized concrete compression at the back-impact face pier bottom, and damage accumulated from the column base towards the column centerline. The mortise-and-tenon joint provided substantial horizontal constraint for the pier, imparting excellent resistance to lateral stiffness. Consequently, both piers showed nearly identical peak impact forces, yet the prefabricated pier exhibited a lesser degree of bending deformation compared to the monolithic one. The depth of the mortise-and-tenon joints was a critical factor affecting the impact response of the prefabricated bridge pier. When the depth reached 0.4D or more, it ensured good impact resistance and joint connection, enhancing energy absorption capability and reducing pier damage. The length of lap-spliced reinforcement significantly affected the overall integrity of prefabricated component connections. Lap lengths of 10d or more greatly reduced the probability of failure in the connection between pier columns and cap beams, lowering damage to the pier columns, joints, and pier cap beams, thus ensuring good impact resistance. The diameter of the lap-spliced reinforcement and the elastic modulus of the grouting material affected the local stiffness near the joints. Increasing the diameter of the lap-spliced reinforcement appropriately prevented excessive local damage, while altering the elastic modulus had minimal impact on improving pier damage.

The Coordinated Control Strategy of Engine Starting Process in Power Split Hybrid Electric Vehicle Based on Load Observation

During the process of moving, the power splitting hybrid vehicle is required to start the engine to transfer from pure electric mode to hybrid drive mode. According to the structural characteristics of the system, the engine starting process was divided into four stages, the engine starting process was established, and a multi-stage engine starting coordination control strategy was designed. In the engine reverse-drag process, the coordination control strategy was transformed into the optimal rotation rate tracker problem. In order to solve the load torque required in the tracking problem, a reduced-order observer was designed. Finally, the validity of the coordination control strategy was verified on the simulation platform of the electro-mechanical composite transmission system. The feasibility of the coordination control strategy was verified by hardware-in-the-loop simulation. The results show that the engine start coordination control strategy could achieve steady and fast engine start control. The maximal impact of the whole vehicle is reduced from 30 to 2.5 m/s3.

Hypercongestion, Autonomous Vehicles, and Urban Spatial Structure

This paper examines the effects of hypercongestion mitigation by perimeter control and the introduction of autonomous vehicles on the spatial structures of cities. By incorporating a bathtub model, we develop a land use model where hypercongestion occurs in the downtown area and interacts with land use. We show that hypercongestion mitigation by perimeter control decreases the commuting cost in the short run and results in a less dense urban spatial structure in the long run. Furthermore, we reveal that the impact of autonomous vehicles depends on the presence of hypercongestion. The introduction of autonomous vehicles may increase the commuting cost in the presence of hypercongestion and may cause a decrease in the suburban population; however, it may make cities spatially expand outward. This result contradicts that of the standard bottleneck model. When perimeter control is implemented, the introduction of autonomous vehicles decreases the commuting cost and results in a less dense urban spatial structure. These results show that hypercongestion is a key factor that can change urban spatial structures. History: This paper has been accepted for the Transportation Science Special Issue on ISTTT25 Conference. Funding: This work was supported by ACT-X [Grant JPMJAX21AE], Fusion Oriented REsearch for disruptive Science and Technology [Grant JPMJFR215M], the Japan Society for the Promotion of Science [Grants 23K13422 and 22H01610], and the Council for Science, Technology and Innovation [Grant JPJ012187]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2024.0519 .

Environmental impact and cost study of vehicles

In the traditional automobile industry, which was dominant from the mid-20th century to the early 21st century, the nitrogen oxides produced by auto mobile exhaust would pollute the air. After entering the 21st century, with lithium batteries as the representative, the energy density of energy storage units has rapidly increased, solving the endurance problem that has plagued the electric vehicle industry for nearly a century. The development path of electric vehicles has become wider and gradually become mainstream products in the market. This paper explores the environmental impact of transitioning from partial to complete tram usage in an urban area with a population of at least 500,000. Initially, this paper calculates the Ecological Evaluation Index to compare the environmental effects of the two types of vehicles. Subsequently, introducing four variables to set the entire model in motion, aiming to predict the environmental conditions of the urban area when entirely reliant on tram services. Furthermore, this paper considers the realistic financial issues that need to be faced and build a model for the financial impact that the transition to pure electric buses will soon bring. The excessive costs and potential external funds caused by the transition, which will affect the final ten-year transformation plan for the city. Finally, this transit company has successfully achieved an operational income of up to 13.3 billion over the past decade even in the absence of government subsidies. This underscores the robust foundation of its financial operations and economic sustainability, providing reliable financial support for future electric bus procurement and maintenance.

Impact of electric vehicles and wave energy systems on OPF of power networks using hybrid Osprey-PSO approach

In this article, a novel optimization algorithm named hybrid Osprey Optimization and Particle Swarm Optimization (OOPSO) is proposed to solve the Probabilistic Optimal Power Flow (POPF) problem in power systems with high penetration of renewable energy resources (RERs), such as photovoltaic, wind, and wave energy and integration of electric vehicles (EVs). The algorithm's results are compared with established optimization algorithms like Osprey Optimization Algorithm (OOA), Particle Swarm Optimization (PSO), and Heap Optimization. Applied to the 30 and 118-bus IEEE test systems, the OOPSO algorithm efficiently deals with the uncertainties produced by RERs generation. This research study includes EV charging profiles for weekdays and weekends. It considers home and work-level charging scenarios. The RERs and EVs penetration ensure system reliability while minimizing generation costs and satisfying power flow constraints. Compared to existing algorithms, the OOPSO algorithm achieves superior performance, faster convergence, and higher solution accuracy. The simulation results show the effectiveness of OOPSO. It appears to be a robust tool for POPF, integrating RERs in power systems with EVs. This work highlights the potential of OOPSO as a feasible approach for power system optimization in the context of RERs and EV integration, paving the way for further research into unconventional grid optimization techniques.

Evaluating the impact of unmanned aerial vehicles (UAVs) on air quality management in smart cities: A comprehensive analysis of transportation-related pollution

Urban environments face significant air pollution challenges affecting health and sustainability. Using unmanned aerial vehicles for air quality monitoring offers a promising solution. This research aims to improve these vehicles' ability to identify pollution sources and develop strategies, with a focus on transportation-related pollution. Detailed air pollution tests revealed that pollutant concentrations surged during morning rush hours, especially in high-traffic coastal areas, while areas away from traffic had much lower levels. Evening tests showed that pollutants from daytime traffic had dispersed throughout the urban area. The consistent northward shift in pollutant concentrations underscored the link between traffic patterns and pollutant distribution. Quantitative analyses and the resulting air pollutant maps showed average increases in pollutant concentrations between morning and evening hours in high-traffic areas: 12.1% for NO2, 5.3% for CO, 9.8% for PM10, and 11.4% for PM2.5. In contrast, the increases in pollutant concentrations in less trafficked urban regions were 45.9%, 48.2%, 32.7%, and 29.5%, respectively. This demonstrates how air pollution originating from areas with heavy traffic impacts other regions through environmental and geographical factors. The findings underscore the need for comprehensive air quality management strategies at the city level, targeting emissions in high-traffic areas and adapting to temporal fluctuations in pollutant levels.

Impact of the traffic on a population of European pond turtles (Emys orbicularis) inhabiting heavily urbanized area at the city of Burgas

We report on the impact of vehicle traffic on a local population of European pond turtles (Emys orbicularis) inhabiting the city of Burgas (Bulgaria). We performed a six-year monitoring program to collect data on the presence of turtles on road E 87 in the south region of the city. The road section splits a Natura 2000 site and crosses through an artificial water basin with fresh to brackish water. We visited the road section in irregular intervals from 3 to over 20 days in the period March to October from 2016 to 2021. For the period of the monitoring, we were able to detect a total of over 300 specimens from all ontogenetic stages (33 juveniles, 74 subadults and 224 adults). During our field surveys in 2016, we detected a total of 47 live and 23 dead adults. In the next years, we found more dead adult turtles than live ones. Similar results were recorded for subadults. In the juveniles, the dead specimens were almost equal to those which were detected alive. Our results indicate an impact of the traffic on the local population of E. orbicularis. We discuss the design and position of constructions, which can mitigate the conflict and reduce the potential for Wildlife-vehicle collisions (WVC).

Analysis of the Impact of Hybrid Power System on Teachers' Psychology and Teaching Environment under Smart Energy Transformation and Energy System Planning

For this paper we study the structure and operational characteristics of plug-in hybrid Vs, Using the life-cycle evaluation method, The analysis model of energy consumption and environmental impact of plug-in hybrid electric vehicle fuel cycle suitable for China's national conditions is established, With the unit mileage of the plug-in hybrid car as the functional unit, Using the whole vehicle NEDC test cycle and combined with the relevant literature, Fuel consumption and environmental emission factors for this functional unit, The fuel cycle energy consumption, conventional gas emissions and greenhouse gas emissions are obtained, Evaluate the effect of power structure change on the above indexes, And compared the plug-in hybrid vehicles with conventional gasoline vehicles and compressed natural gas vehicles. As follows: compared with the current technical level of gasoline cars, under the background of road traffic, plug-in hybrid car fuel consumption is reduced by 40.7% less than gasoline cars, VOC, NOx, SO2 and greenhouse gas emissions than traditional gasoline vehicles reduced by 31.5%, 15.2%, 66.7% and 55.8%, this to alleviate increasingly severe urban air pollution is of great significance. Plug-in hybrid vehicles offer advantages over traditional gasoline cars in terms of energy consumption and emissions, both at the vehicle level and throughout the fuel cycle. Energy consumption is 56.3% lower, including a 56.4% reduction in crude oil usage, reducing oil dependency and promoting energy security. Environmentally, plug-in hybrids emit significantly less than gasoline cars, with VOC, NOx, SO2, PM10, and CO emissions reduced by up to 56%. Greenhouse gas emissions, including N2O, CH4, and CO2, are also lower. Additionally, emissions tend to be concentrated upstream, facilitating centralized pollution control.

Investigating the Impacts of Autonomous Vehicles on the Efficiency of Road Network and Traffic Demand: A Case Study of Qingdao, China.

Rapid urbanization has led to the development of intelligent transport in China. As active safety technology evolves, the integration of autonomous active safety systems is receiving increasing attention to enable the transition from functional to all-weather intelligent driving. In this process of transformation, the goal of automobile development becomes clear: autonomous vehicles. According to the Report on Development Forecast and Strategic Investment Planning Analysis of China's autonomous vehicle industry, at present, the development scale of China's intelligent autonomous vehicles has exceeded market expectations. Considering limited research on utilizing autonomous vehicles to meet the needs of urban transportation (transporting passengers), this study investigates how autonomous vehicles affect traffic demand in specific areas, using traffic modeling. It examines how different penetration rates of autonomous vehicles in various scenarios impact the efficiency of road networks with constant traffic demand. In addition, this study also predicts future changes in commuter traffic demand in selected regions using a constructed NL model. The results aim to simulate the delivery of autonomous vehicles to meet the transportation needs of the region.

Reshaping cyclist mobility: Understanding the impact of autonomous vehicles on urban bicycle users

Autonomous Vehicles (AVs) present a jarring new normal for negotiation on public streets. Current communication and interaction stand to be disrupted with the presence of AVs. Active transport users, specifically bicycle users, rely on human communication and subtle cues to feel confident when negotiating with other road users. Shifts in communicability with AVs presents a unique challenge for bicycle users. It remains unclear how AVs will impact urban bicycle users. This paper employs a mixed-methods approach to understanding impacts that AVs have on urban bicycle users in four test sites with varying levels of traffic stress. Interviews and focus groups were used across different traffic stress scenarios in three countries to understand how bicycle users will be impacted by AVs in real-world scenarios. The results represent a pioneering cross-section of four bicycle cultures’ exposure to AVs. Results universally show that, compared to conventionally operated vehicles, an enduring sense of unease remains unresolved with AVs and that shifting focus to bicycle user experiences and prioritizing the needs of a diverse population of non-occupants will be critical. If AVs are not deployed responsibly and responsively, they could turn bicycle users away from cycling in a streetscape where active transport users are already marginalized.

Revolutionizing logistics: The impact of autonomous vehicles on supply chain efficiency

This review paper assesses the impact of autonomous vehicles (AVs) on enhancing the efficiency of supply chains, aiming to synthesize existing research and identify future research directions. Through a comprehensive analysis of literature spanning technological, economic, and regulatory perspectives, this paper maps the current landscape of AV integration in logistics. The review finds that AVs offer substantial improvements in supply chain efficiency through continuous operation and reduced human error, leading to decreased costs and improved delivery timelines. It details the potential for up to 30% enhancement in logistical operations with AV adoption. Critical barriers such as technological challenges, regulatory concerns, and cybersecurity risks are also discussed. Conclusively, the paper argues that while AVs present a promising avenue for revolutionizing supply chain management, their widespread adoption depends on overcoming existing barriers. It calls for targeted research into robust AV systems, supportive policy frameworks, and stakeholder engagement strategies to fully realize their benefits.

Comparing the circularity and life cycle environmental performance of batteries for electric vehicles

Batteries account for a significant share of the life cycle impact of electric vehicles (EV). Nonetheless, the circularity and environmental performance of EV batteries remains underexplored in the literature. This paper compares the circularity (Circularity Index and Product Circularity Indicator) and environmental performance (Global Warming Potential (GWP) and Abiotic Depletion Potential of minerals (ADPm)) of lithium nickel manganese cobalt (NMC) and lithium iron phosphate (LFP) batteries subjected to pyrometallurgy and hydrometallurgy recycling. Lifetime extension, improved energy efficiency, and material recovery ratios were also calculated to identify the optimal battery design. The findings show that NMC batteries are 6–25% more circular and environmentally sustainable (<4–6% GWP and <13–16% ADPm) than LFP batteries, primarily due to better material recovery ratios. Moreover, the longer lifetime of LFP does not sufficiently offset resource and environmental impacts. Finally, the study discusses the results to support circular and environmental innovation in EV battery design.

Dual layer energy management model for optimal operation of a community based microgrid considering electric vehicle penetration

This work develops a dual-layer energy management (DLEM) model for a microgrid (MG) consisting of a community, distributed energy resources (DERs), and a grid. It ensures the participation of all these energy entities of MG in the market and their interaction with each other. The first layer performs the scheduling operation of the community with the goal of minimizing its net-billing cost and sends the obtained schedule to the DER operator and grid. Further, the second layer formulates a power scheduling algorithm (PSA) to minimize the net-operating cost of DERs and takes into account the load demand requested by the community operator (COR). This PSA aims to achieve optimal operation of MG by considering solar PV power, requested demand, per unit grid energy prices, and state of charge of the battery energy storage system of the DER layer. Moreover, to study the impact of electric vehicles (EVs) load programs on DLEM, the advanced probabilistic EV load profile model is developed considering practical and uncertain events. The EV load is modelled for grid to vehicle mode, and a new mode of EV operation is introduced, i.e., vehicle to grid with EV demand response strategy (V2G_DRS) mode. The solar PV and load demand data are obtained from the MG setup installed and buildings present at the university campus. However, a scenario reduction technique is used to deal with the uncertainties of the obtained data. In order to evaluate the efficacy of the developed DLEM, its results are compared to previously reported energy management models. The results reveal that DLEM is superior to the existing models as it decreases the net-billing cost of COR by 13% and increases the profit of the DER operator by 17%. Further, it is found that for the highest EV penetration, i.e., 30 EVs, the V2G_DRS mode of EV operation reduces the total energy imported by COR by 11.39% and the net-billing cost of COR by 7.88%. Therefore, it can be concluded that the proposed model with the introduced V2G_DRS mode of EV makes the operation of all the entities of MG more economical and sustainable.

Stochastic Optimal Strategies and Management of Electric Vehicles and Microgrids

This study combines the Nash–Cournot competition model and the stochastic optimization model to examine the impact of electric vehicle (EV) quantity fluctuations on microgrid operations, aiming to optimize energy usage in a competitive electricity market. Integrating distributed energy resources and bidirectional charging, microgrids offer a novel approach for energy optimization, aiding in renewable energy generation, peak demand management, and emission reduction. Empirical evidence highlights benefits in Taiwan’s electricity market and net-zero emissions target by 2050, with a case study demonstrating enhanced local renewable energy generation due to EVs and microgrid integration. As the number of EVs increases, electricity sales from microgrids decline, but electricity purchases remain stable. The degree of electricity liberalization also influences the supply and demand dynamics of the electricity market. Microgrids selling electricity only to the main grid increases total power consumption by 65.55 million MWh, reducing the market share of the state-owned utility (Taipower). Conversely, allowing retailers to purchase from microgrids increases total consumption by 30.87 million MWh with a slight market share decrease for Taipower. This study contributes to providing an adaptable and flexible general model for future studies to modify and expand based on different scenarios and variables to shape energy and environmental policies.