Green Vehicle Research Articles

Anthropological Evaluation of Social Perception and Use of Green-Electric Vehicles in Terms of "Environmentalism"

The new solutions always come with new problems. The rise of green vehicles has been heralded as a significant step towards reducing the environmental impact of transportation. Electric vehicles, hybrids, and other eco-friendly alternatives have gained popularity in recent years, with promises of reduced emissions and a greener future. However, the question remains: Are green vehicles truly environmentally friendly? This comprehensive academic article delves into the environmental impact of green vehicles, considering factors such as manufacturing, energy sources, real practical use of vehicles, and their overall carbon footprint. By examining the lifecycle of green vehicles, we aim to provide a balanced assessment of their environmental benefits and challenges.

A Conceptual Level on Green Computing Applications on Eco-Friendly Approaches

The Green computing will work in this field as a life saver to environment as green computing will reduce energy usage by using various green computing eco-friendly approaches like-green design, green awareness, green standards, green disposals, green manufacturing and green usage which therefore help in the less emission. The "Going Green" is a rising trend establishing itself as the preferred way of doing things while saving the environment. This now appears in a large number of aspects in our lives, such as recycling, energy-efficient devices, clean energy sources, eco-friendly vehicles, green buildings. Computing has also established its share to contribute to saving the environment under the concept "Green Computing". Green computing is the environmentally responsible and eco-friendly use of computers and their resources. In broader terms, it is also defined as the study of designing, engineering, manufacturing, using and disposing of computing devices in a way that reduces their environmental impact. Green Computing, also known as Green Technology or Green IT, has quickly emerged as the most effective means of utilising technology.

An innovative virtual sensing system for the vehicle-centric evaluation of emissions in the sustainable mobility transition

The objective of the research is to develop a new methodology capable of quantifying the emissions of internal combustion engine cars based not only on their technology but also on the dynamic behavior of the individual vehicle. No complicated exhaust measurement apparatus is needed. Employing just a telematic device equipped with GNSS and an inertial measurement unit, which can be easily attached to the vehicle, we demonstrate how individualised, accurate climate-altering emissions result by using figures extracted from European test databases, appropriately combined with real travelled distances, speeds, and driving style of each individual car. Pollutant emissions are, in this paper, also assessed though in a more general manner, and this represents a starting point for a future complete vehicle-centric emissions evaluation. This research demonstrates that circulating car emissions have to be assessed considering not only the Euro class and type of fuel, but also how the vehicle is driven. In this work a new, implementation oriented methodology is proposed in order to properly merge average European standard emission data with car-based telematic measures to highlight a new paradigm for regulating in a more conscious way the transition of the internal combustion engine car park towards a large scale, sustainable mobility ecosystem. This approach would place greater responsibility on the driver, without leaving anyone behind and without compelling the car scrapping solely based on the Euro class of its engine. The key contribution is ultimately to establish an easy to handle methodology enabling targeted and behavior-based traffic management policies. In fact, through a massive telematics recent dataset, the proposed virtual emission sensing system reveals that an extensive and inefficient use of eco-friendly vehicles produces much more greenhouse gas emissions than older vehicles driven in an environmentally responsible way.

A study on the multi layers of automotive interior trim parts to improve the acoustic performance with microfiber applied to the surface layer

As the world joins environmental regulations, there is an increasing demand for the production of eco-friendly cars. As a result, the driving method of the vehicle was changed from the engine to the electric motor, and the main noise source was changed. In case of existing internal combustion engines (ICE), the low-frequency sound range, which is the engine's main noise, is the main source of sound. As it is converted into an eco-friendly car, the noise that was hidden by the engine combustion sound and the high-frequency noise of the motor are being highlightened. PP meltblown generally has a lower denier than other fibers, so it is effective in improving sound absorption performance because the surfaces of the fibers are large compared to the same weight of another fibers. In conclusion, by applying this PP meltblown fibers to the structure of Dash Insulation, sound absorption performance is improved and resulting in lightweighten effect of Dash Insulation

Exploring realistic vehicle acceleration sounds through discomfort index analysis

Contemporary Japanese society's heavy reliance on automobiles is shifting from transportation to leisure, amidst rising environmental concerns over emissions. This has led to a pivot towards eco-friendly options, notably clean diesel vehicles (DVs) and electric vehicles (EVs), due to Europe's stringent regulations. DVs aim to lower harmful emissions, while EVs are favored for their minimal emissions and silent operation. However, EVs' lack of audible acceleration noise poses safety risks, as drivers may struggle to perceive speed changes. The study investigated how deviations in expected engine sounds impact perceived sound quality and vehicle performance assessment, focusing on DV and EV acceleration sounds. It explored the integration of certain sensations (rumbling, booming, humming) into EV sounds to enhance realism, assessing comfort levels among drivers with varying experience.

Income moderates the nonlinear influence of built environment attributes on travel-related carbon emissions

Policymakers have adopted built environment policies to modify people's travel behavior and the related emissions. However, few studies have examined the interactive impact between income level and built environment attributes on travel-related carbon emissions (TCE), and only several studies consider their nonlinear relationships. With data from the Twin Cities, US, this study estimated the nonlinear effects of built environment attributes and demographics on TCE. It further examined the interactive impacts between household income and built environment attributes. The findings highlight that demographics exert a greater influence on TCE than the built environment. Employment status, job accessibility, and gender are the most important predictors. Besides individual nonlinear relationships, household income and built environment attributes have salient interactive impacts on TCE. The results suggest that providing environment friendly and affordable transportation choices to low-income population, switching to clean energy vehicles, and offering more matched job opportunities to low-income population near their residence are promising to create a sustainable transportation system.

A two-phase algorithm for the dynamic time-dependent green vehicle routing problem in decoration waste collection

Transportation activities associated with construction waste generate substantial carbon emissions, an issue that is attracting increasing environmental concern. To raise construction waste transportation efficiency and reduce carbon emission, we address the dynamic time-dependent green vehicle routing problem for decoration waste collection (DTDGVRP-DWC). In the existing literature, many deterministic approaches to the dynamic vehicle routing problem are myopic, as they only react to already arrived requests. In this paper, we propose a stochastic sampling method to tackle with uncertain customer request in the real world. The DTDGVRP-DWC is formulated as an 0-1 programming. In the new model, we consider urban traffic congestion and variable speeds over time, and factors that significantly influence both carbon emissions and fuel costs. To quickly solve the complicated optimization problem, we develop a two-phase algorithm. In the first phase, we embed a competitive simulated annealing algorithm to determine visitation schedules for anticipated and early-request customers. In the second phase, we propose an event-trigger mechanism to decompose the dynamic problem into a series of static sub-problems, and an effective heuristic to solve each sub-problem. Computational results show that as long as the prediction accuracy exceeds a threshold, the forecast routing method consistently performs better than reactive routing. A real-world case demonstrates that an early commitment waiting time strategy benefits timely service requirements, whereas a late or hybrid waiting time strategy takes overall efficiency and customer satisfaction into account.

Efficiency maximization of fuel cell electric bus using asymmetric multi-stack fuel cells

Fuel cell electric vehicles (FCEVs) have been widely studied as alternative ecofriendly vehicles based on multi-stack fuel cell (MFC) systems. An MFC system has the advantages of considerable efficiency, reliability, and durability compared with a single-stack fuel cell system. In this study, a novel MFC concept with an asymmetric structure is proposed to maximize the efficiency of a fuel cell electric bus (FCEB). The proposed concept was designed with a cascade electrical architecture composed of differently rated power stacks, and the optimal energy distribution between the stacks was determined to leverage the asymmetric structure. This facilitates the use of high-efficiency areas of the fuel cell stacks throughout most of the output power range. To confirm the performance of the proposed mechanism, dynamic programming, a global optimization technique, was used as the energy management strategy, and the FCEB was tested on Manhattan, Hanoi, and Seoul bus driving cycles. As a result, a significant reduction in the total fuel consumption of the proposed MFC electric bus compared with that of the conventional FCEB was verified.

Research progress of aerogel used in lithium-ion power batteries

In recent years, with the rapid development of clean energy vehicles (i.e., electric vehicles and hybrid electric vehicles) and electrochemical energy storage stations, safety accidents have significantly increased. However, the abuse conditions such as overheating, overcharging, mechanical abuse, short circuits, etc., can result in thermal runaway of lithium-ion batteries (LIBs). Severe thermal runaway can lead to battery fire and even explosion, thereby threatening the safety of personnel. The application of a few aerogels to the thermal insulation layer between the cells of the lithium-ion battery modules can strengthen the safety of batteries. Among many aerogels, oxide aerogels show excellent insulation and high-temperature resistance. Therefore, aerogels, especially oxide aerogels, have aroused widespread research interest. This paper introduces the mechanism of thermal runaway of LIBs and systematically reviews several important oxide aerogels and the derived composites, especially those based on SiO2, Al2O3, and ZrO2 aerogels. The mechanical strength and high-temperature resistance of those aerogels are discussed. The application of aerogel in LIBs is also investigated in detail, and the all-around effect is caused by the introduction of aerogel materials. In addition, the thermal protection safety strategy of aerogel thermal insulation layers is proposed. It is supposed that this review could enable readers to deepen their understanding of this field.

Satyadarshan Technologies & Services: revolutionizing urban mobility?

Learning outcomes After reading and analyzing this case study, students will be able to describe the challenges of creating an electric vehicle (EV) start-up with the objective of zero-carbon emissions, identify opportunities and challenges for Satyadarshan Technologies & Services (STS) in enhancing the B2B customer base and sales volumes in the EV market, identify and assess government incentives to reinforce STS’s existing EV business and compose an understanding of and determine an ability to use various industrial marketing and promotion strategies for STS in the present environment. Case overview/synopsis STS was launched in 2020 to provide environmentally conscious urban commuting. Himanshu Purohit, the founder of STS, commenced an e-bicycle assembly unit and produced the first advanced electric drivetrain technology. The vision was to transform how people viewed mobility and make EVs the standard for a healthier globe. Nurturing a start-up with zero-carbon emissions was tedious due to limited infrastructure, high costs, low market acceptance and supply chain constraints. With the relentless pursuit of excellence, STS constantly pushed the boundaries and crossed the break-even ceiling in the year 2022. As a budding player in the souk, the company expected to gain a strong presence in the EV market with particular attention to the B2B customer segment. At the same time, the company aimed to ensure business sustainability by leveraging government incentives. The company needed to expand its corporate sales volume and craft a sustainable competitive advantage. Purohit recognized various challenges to the sustainability of STS that stood between the company's goals and their realization, particularly in achieving a sustainable move in the EV segment. Consequently, Purohit found himself at a critical juncture to pave the path toward the growth of the start-up. Eventually, analysis of the company's business challenges, industrial marketing and promotional strategies required strategic planning to appraise and evaluate the business model. Complexity academic level This case study is designed for new-age Master of Business Administration and executive management programs. It should be used in entrepreneurship and strategic management courses to discuss small innovative e-bike start-ups. This includes conducting a competitive analysis and self-assessing a firm's market-oriented strategies. Prima facie, undergraduate and postgraduate students are beneficiaries of this case. This case study may also be conducive to teaching how to initiate a sustainable and green vehicle business. This case study guides students entering the EV business, addressing industry-specific challenges and conducting market analysis. Supplementary materials Teaching notes are available for educators only. Subject code CSS 3: Entrepreneurship.

A Path Planning Method Based on Hybrid Sand Cat Swarm Optimization Algorithm of Green Multimodal Transportation

Aiming at the difficulty of measuring various costs and time-consuming elements in multimodal transport, this paper constructs a green vehicle comprehensive multimodal transport model which incorporates transportation, transit, quality damage, fuel consumption, and carbon emission costs and proposes a hybrid embedded time window to calculate the time penalty cost in order to reflect the actual transport characteristics. Furthermore, in order to better solve the model, a hybrid sand cat swarm optimization (HSCSO) algorithm is proposed by introducing Logistic–Tent chaotic mapping and an adaptive lens opposition-based learning strategy to enhance the global search capability, and inspired by the swarm intelligence scheme, a momentum–bellicose strategy and an equilibrium crossover pool are introduced to improve the search efficiency and convergence ability. Through testing nine benchmark functions, the HSCSO algorithm exhibits superior convergence accuracy and speed in dealing with complex multi-dimensional problems. Based on the excellent global performance, the HSCSO algorithm was utilized for multimodal vehicle transportation in East China, and a path with a lower comprehensive cost was successfully planned, which proved the effectiveness of the HSCSO algorithm in green intermodal transport path planning.

Uncharted depths: Navigating the energy security potential of deep-sea mining

In the context of a global shift towards low-carbon energy systems, this paper provides an in-depth analysis of deep-sea mining's (DSM) potential role in enhancing global energy security. Addressing the growing demand for critical minerals essential for clean energy technologies, electric vehicles (EVs), and energy storage systems, the paper examines how DSM can diversify the global mineral supply and reduce reliance on geopolitically sensitive sources. It explores DSM's capacity to recalibrate energy prices, influence the competitive landscape of clean energy technologies, and shift geopolitical dynamics. The paper delves into the multi-faceted impacts of DSM on energy security, including geopolitical shifts, supply chain diversification, and environmental trade-offs. By providing a holistic view that links mineral supply security to sustainable energy transitions, this study extends beyond prior research focused mainly on the technical and environmental aspects of DSM. The findings illustrate DSM's intersection with international politics, its effect on energy pricing strategies, and the balance between resource exploitation and environmental stewardship. Strategic policy recommendations are offered to optimize DSM's benefits while minimizing its ecological impacts, aligning the emerging DSM industry with global sustainability goals. In addition to identifying challenges, the paper proposes actionable solutions, contributing a unique perspective to the discourse on DSM and energy security.

Efficiency Analysis of Powertrain for Internal Combustion Engine and Hydrogen Fuel Cell Tractor According to Agricultural Operations.

As interest in eco-friendly work vehicles grows, research on the powertrains of eco-friendly tractors has increased, including research on the development of eco-friendly vehicles (tractors) using hydrogen fuel cell power packs and batteries. However, batteries require a long time to charge and have a short operating time due to their low energy efficiency compared with hydrogen fuel cell power packs. Therefore, recent studies have focused on the development of tractors using hydrogen fuel cell power packs; however, there is a lack of research on powertrain performance analysis considering actual working conditions. To evaluate vehicle performance, an actual load measurement during agricultural operation must be conducted. The objective of this study was to conduct an efficiency analysis of powertrains according to their power source using data measured during agricultural operations. A performance evaluation with respect to efficiency was performed through comparison and an analysis with internal combustion engine tractors of the same level. The specifications of the transmission for hydrogen fuel cell and engine tractors were used in this study. The power loss and efficiency of the transmission were calculated using ISO 14179-1 equations, as shown below. Plow tillage and rotary tillage operations were conducted for data measurement. The measurement system consists of four components. The engine data load measurement was calculated using the vehicle's controller area network (CAN) data, the axle load was measured using an axle torque meter and proximity sensors, and fuel consumption was measured using the sensor installed on the fuel line. The calculated capacities, considering the engine's fuel efficiency for plow and rotary tillage operations, were 131.2 and 175.1 kWh, respectively. The capacity of the required power, considering the powertrain's efficiency for hydrogen fuel cell tractors with respect to plow and rotary tillage operations, was calculated using the efficiency of the motor, inverter, and power pack, and 51.3 and 62.9 kWh were the values obtained, respectively. Considering these factors, the engine exhibited an efficiency of about 47.9% compared with the power pack in the case of plow tillage operations, and the engine exhibited an efficiency of about 29.3% in the case of rotary tillage operations. A hydrogen fuel cell tractor is considered suitable for high-efficiency and eco-friendly vehicles because it can operate on eco-friendly power sources while providing the advantages of a motor.

A cold start strategy in fuel cell vehicles to provide instant hot air for stacks and passengers by vortex tubes

Green vehicles, particularly Fuel Cell Vehicles (FCVs), offer a promising solution to environmental challenges. One of the major obstacles for FCVs is starting the Polymer Electrolyte Membrane (PEM) fuel cell stacks in subfreezing temperatures, where the water produced by chemical reactions can freeze and hinder the cold-start process. Preheating the inlet air to the stack up to 80 °C is an effective approach to overcome this issue. However, conventional heating systems, such as electric heaters, are unable to heat the air quickly enough. This paper introduces a novel heating method to enhance the cold-start capability of FCVs. The proposed solution involves integrating vortex tubes, which are simple and cost-effective, with the vehicle’s existing compressor. This system not only preheats the inlet air to the stacks but also provides warm air for the passengers simultaneously. By developing a 3D-CFD model of the vortex tube, the results demonstrate that the system can preheat the inlet air to the stacks from −30 °C to 80 °C and the air entering the passenger compartment from −30 °C to nearly 37 °C in just about 5 s. In comparison, conventional heating systems require over 600 s (10 min) to achieve the same temperature rise.

Revealing How Much Drivers Understand about Vehicle Pollutants: Towards Development of Information Campaigns

Thirty-four interviews were carried out with drivers in four countries to elicit their understanding about pollutants, specifically nitrogen dioxide (NOX) and particulate matter (PM). The results showed that most of the participants knew that cars emitted carbon dioxide (CO2), but they were less aware of the emission of NOx and PM. Also, being aware of the negative impacts of pollutants did not necessarily lead to eco-friendly vehicle choices. Most of the drivers were aware of pollutant friendly behaviours such as avoiding harsh acceleration/deceleration and maintaining smooth speed but were unaware of behaviours such as efficient gear use, avoiding engine idling, or anticipation of traffic ahead. Only a few mentioned pre-trip or strategic level behaviours (e.g., vehicle size/weight or the selection of appropriate routes and avoidance of traffic congestion). The results could be used to design educational material to raise awareness and provide drivers with tips to reduce their pollutant emissions.

Dynamic delay-based game approach in car and petrol supply chains under government intervention

Effective decision-making in a temporal context is challenged by the enduring impacts of delays, where decisions made in a certain period are influenced by choices made in preceding periods. This paper delves into the analysis of decision-making in a dynamic game system characterized by delay impact on decisions. Notably, it pioneers the application of a game approach to detect the intricate relationship between car and petrol supply chains operating under conditions of dynamism and uncertainty. The marginal profit method is applied to deal with the dynamic game model. Furthermore, this article investigates the improvement of green car levels, on member profits. In the car supply chain, the car manufacturer sells two distinct product types: green and regular. In this paper, green cars refer to cars with low petrol consumption, and as gas consumption decreases, the green level of the car ascends. This study marks the first instance where optimal production capacity allocation is examined within the framework of delay and uncertainty. Considering the government's initiative to curtail petrol consumption in automobiles, the effects of the government's supporting role are also analyzed in this paper. As a result, the greenness level witnessed a 4.1-fold increase, leading to an 81.7% surge in the demand for green cars, consequently boosting the profit of the entire car supply chain. Several numerical experiments of a real case were examined to evaluate the performance of the proposed models. Finally, some sensitivity analyses were applied to the principal parameters of the model to extract managerial insights.

Do climate change risks affect the systemic risk between the stocks of clean energy, electric vehicles, and critical minerals? Analysis under changing market conditions

This paper analyzes the impact of climate change risks—specifically from natural disasters, global warming, international summits, and U.S. climate policy—on the return connectedness (systemic risk) of a network consisting of the stocks of clean energy, electric vehicles, and critical minerals in bear, bull, and normal market conditions. Employing a quantile vector autoregression (QVAR) approach, we find significant temporal variations in the total connectedness index, with notable spikes during the COVID-19 pandemic and the Russia-Ukraine war. Total connectedness is higher but less variable under bear and bull market conditions. Concerns about global warming has a positive and significant impact on systemic risk during bear and normal market conditions while international summits have a negative impact during normal market conditions. However, the effects of these climate change risks are small in magnitude. Economic policy uncertainty and stock market volatility have the largest positive impacts on systemic risk under most market conditions. Our results reveal a nonlinear (inverted U-shaped) relationship between variable importance and systemic risk quantile, showing that the impact on connectedness is largest in magnitude under normal market conditions.

An Experimental Analysis on Performance Assessment of Green Vehicles with Integration of Green Energy

An Experimental Analysis on Performance Assessment of Green Vehicles with Integration of Green Energy

Optimization research on multi-trip distribution of reverse logistics terminal for automobile scrap parts under the background of sustainable development strategy

To effectively solve the reverse logistics distribution problem caused by the increasing number of scrapped parts in the automotive market, this study constructs a multi-trip green vehicle routing problem model with time windows by comprehensively considering the coordination between carbon dioxide emissions and cost efficiency. A hybrid adaptive genetic algorithm is proposed to solve this problem, featuring innovative improvements in the nearest neighbor rule based on minimum cost, adaptive strategies, bin packing algorithm based on the transfer-of-state equation, and large-scale neighborhood search. Additionally, to efficiently obtain location data for supplier factory sites in the distribution network, a coordinate extraction method based on image recognition technology is proposed. Finally, the scientific validity of this study is verified based on the actual case data, and the robust optimization ability of the algorithm is verified by numerical calculations of different examples. This research not only enriches the study of green vehicle routing problems but also provides valuable insights for the industry to achieve cost reduction, efficiency enhancement, and sustainable development in reverse logistics.

Are South Korea’s Environmental Policies Rational? An Analysis Focusing on Fine Dust Programs in the Seoul Metropolitan Area

Since 2018, the government of South Korea has strengthened its environmental policies to solve the problem of fine particulate matter in the air. Because of these strict regulations, diesel cars have been replaced with cleaner vehicles, and coal power plants have been shut down. Despite these government efforts, some researchers assert that fine dust programs have failed in Seoul, the capital of Korea. In other words, they conclude that the central and local governments designed and implemented the policies unreasonably. Despite these critics, this study attempts to prove that the government has thoroughly and meticulously prepared its policies on fine particles. Also, it tries to demonstrate that the policy scheme has been properly established. To attain these research goals, the theory of procedural rationality is adopted and utilized. As a result of the analysis, six steps of procedural rationality were identified in the Korean policy on fine dust: problem identification, goal setting, searching for alternatives, consequence prediction, comparison of alternatives, and policy decision. In conclusion, this study provides suggestions for environmental policies in other metropolitan cities, especially in developing countries that suffer from severe air pollution.