EV Adoption Research Articles

A Detailed Analysis of Electric Vehicle Technology Advancements and Future Prospects

Abstract: The development of electric vehicles has surged in several nations in an effort to lessen reliance on oil and environmental damage[1]. A solution to the energy crisis and environmental problems is the adoption of EVs, particularly battery electric vehicles. This study offers a thorough analysis of the technical advancement of EVs and new technologies for use in the future. EV charging infrastructure, electric motors, batteries, charging technology, and electric motor control are all briefly discussed. As an additional contribution, this study also emphasises the technological difficulties and cutting-edge technologies for the future advancement of EV safety, dependability, and efficiency.

Evaluation and analysis of the improvement in charging time for the high-power fast charging module using phase change material

The advancement of charging time for the fast charging piles facilitates the full adoption of EVs. The benefits of adding the suitable phase change material (PCM) to the thermal control system of the high-power fast charging power module are demonstrated in this experimental study. The effects of different PCM's melting temperature, thermal conductivity, and filling thickness on the improvement of charging time are explored, and the PCM melting rate is visualized to reveal the mechanism of PCM in improving the charging time. The results show that the extension in charging time of 2370 s is found for the charging power module coupled with PCM at the heat generating power of 15 W, and it is extended by 54% and 39% at heat generating power of 25 W and 35 W, respectively. The benefit of applying the PCM in the improvement of charging time for the charging power module is lessened with increasing the air velocity. The optimal PCM melting temperature is 47.5 °C, and it achieves the maximum charging time of 1540 s. The maximum available charging time is 1620 s at the filling PCM thickness of 5.5 mm. Also, the charging time is extended by 510 s when the thermal conductivity of PCM increases from 0.2 W/(m K) to 5 W/(m K). Increasing the heat generating power or decreasing the air velocity will shorten the completed melting time of the used PCM, and the initial melting time is also ahead. A faster PCM melting rate is observed at the lower PCM melting temperature and filling thickness, and this shortens the PCM latent heat role in the thermal control for the charging power module.

Optimal Deployment of Electric Vehicles’ Fast-Charging Stations

As climate change has become a pressing concern, promoting electric vehicles’ (EVs) usage has emerged as a popular response to the pollution caused by fossil-fuel automobiles. Locating charging stations in areas with an expanding charging infrastructure is crucial to the accessibility and future success of EVs. Nonetheless, suitable planning and deployment for EV fast-charging stations is one of the most critical determinants for large-scale EV adoption. Installing charging stations in existing fuel/gas stations in the city may be an effective way to persuade people to adopt EVs. In this paper, we aim to optimally locate a fast-charging station in an existing gas station in the real-world scenario of Aichi Prefecture, Japan. The purpose is to locate and size fast-charging stations in such ways that drivers can get access to these charging facilities within a rational driving range while considering real-world constraints. Furthermore, we include the investment cost and the EVs users' convenience cost. This problem is formulated by five integer linear programming using a weighted set covering models. The developed model determines where to locate charging stations as well as how many chargers should be installed in each charging station. The experimental results demonstrate that an appropriate location scheme can be obtained using the model M 5 . A computational experiment identifies the best infrastructure solutions for policymakers to consider in the context of growing environmental policies.

Battery Swapping Stations- A Viable Option for Faster Adoption of EVs in India

Total electrification of road transport has its own major constraints. The industry struggles to reduce the plug-in charging times and impact on the grid of battery-powered electric vehicles. Battery swapping is one of the best concepts to overcome the constraints where Vehicles swap low state charge batteries for charged ones at Battery Swapping Stations (BSS). A Battery Swapping Stations (BSS) is a charging place/fuelling station equipped with number of standards and certified charging units and battery swapping robots. A BSS has a certain amount of battery inventory of fully charged batteries of different sizes and types thus providing a faster and intermediate service to the customer looking for recharging their batteries. This paper studies the challenges and opportunities for the use of BSS in India.

GridShield—Optimizing the Use of Grid Capacity during Increased EV Adoption

With the increasing adoption rate of electric vehicles, power peaks caused by many cars simultaneously charging on the same low-voltage grid can cause local overloading and power outages. Smart charging solutions should spread this load, but there is a residual risk of incidental peaks. A decentralized and autonomous technology called GridShield is being developed to reduce the likelihood of a transformer’s fuse blowing when other congestion solutions have failed. It serves as a measure of last resort to protect the grid against local power failures from unpredicted congestion by temporarily limiting the virtual capacity of charging stations. This paper describes the technical development and demonstrates how GridShield can keep a transformer load below a critical limit using simulations and real-world tests. It optimizes grid capacity while ensuring grid reliability.

Architecture for Co-Simulation of Transportation and Distribution Systems with Electric Vehicle Charging at Scale in the San Francisco Bay Area

This work describes the Grid-Enhanced, Mobility-Integrated Network Infrastructures for Extreme Fast Charging (GEMINI) architecture for the co-simulation of distribution and transportation systems to evaluate EV charging impacts on electric distribution systems of a large metropolitan area and the surrounding rural regions with high fidelity. The current co-simulation is applied to Oakland and Alameda, California, and in future work will be extended to the full San Francisco Bay Area. It uses the HELICS co-simulation framework to enable parallel instances of vetted grid and transportation software programs to interact at every model timestep, allowing high-fidelity simulations at a large scale. This enables not only the impacts of electrified transportation systems across a larger interconnected collection of distribution feeders to be evaluated, but also the feedbacks between the two systems, such as through control systems, to be captured and compared. The findings are that with moderate passenger EV adoption rates, inverter controls combined with some distribution system hardware upgrades can maintain grid voltages within ANSI C.84 range A limits of 0.95 to 1.05 p.u. without smart charging. However, EV charging control may be required for higher levels of charging or to reduce grid upgrades, and this will be explored in future work.

Anticipating the impacts of light-duty vehicle electrification on the U.S. automotive service workforce

Abstract This paper draws on publicly available data from the Current Population Survey and the Bureau of Labor Statistics, as well as estimates from 25 studies, to understand how a transition to electric vehicles may impact workers in the vehicle services sector. We examine the structure of the current vehicle service workforce, characterize its unique vulnerabilities along several dimensions, and evaluate how it may be impacted by rising EV adoption. Careful attention to how the benefits and costs of widespread vehicle electrification are distributed is essential to inform effective policy to support workers and communities through an EV transition, and this analysis provides a starting point for understanding these impacts. More generally, the case of vehicle service workers suggests that understanding indirect, system-wide impacts of the broader clean energy transition may inform a more just transition, which may in turn help to maintain and expand support for necessary climate action.

Implications of the energy transition for government revenues, energy imports and employment: The case of electric vehicles in India

Whereas the environmental benefits of transitioning away from fossil fuels are becoming indisputable, the implications for government revenues, employment, balance of trade, and employment appear less clear. Using an accounting-like framework, we analyze the potential near to medium-term implications of electric vehicles displacing internal combustion engine (ICE) vehicles. Total cost of ownership (TCO), imports, government revenues, employment and greenhouse gas (GHG) emissions are each lower with EVs under different market and policy scenarios considered. An exception is a steep fall in oil prices (say by 50% from current levels), which increases net energy imports when battery cells are imported. Targeting high usage vehicles for EV adoption amplifies reduction in TCO, GHG emissions and imports but also leads to greater reduction in tax revenues. Furthermore, foregone tax revenues from avoided fossil fuel consumption is several times greater than the subsidies to EVs in the form of preferential tax rates. On a per vehicle basis, each fossil fuel vehicle generates over six-fold greater taxes over its life relative to an EV. Whereas economic growth and public policy can mitigate adverse impacts on government revenues and employment, simultaneously reducing total emissions as well will, if history is a guide, be more challenging.

Integrating Diffusion of Innovations and Theory of Planned Behavior to Predict Intention to Adopt Electric Vehicles in Rwanda

Purpose: Integration of the theory of planned behaviour and the Diffusion of innovations (DOI) theory to examine EVs low adoption intention in Rwanda.
 Methodology: The research model involved the integration of the Theory of planned behaviour and the Diffusion of innovation. To build the conceptual framework, over 50 articles were collected from Google scholar and summarised using meta-analysis. Two hundred and twenty participants were surveyed in person using a questionnaire, with each construct having at least three questions to run the Partial least squares (PLS) Structural Equation Modelling (SEM). Data were analysed using SmartPLS 4.0.
 Findings: The study found that two factors of the Theory of planned behaviour TPB- attitudes and perceived behavioural control- positively impact EVs adoption intention while subjective norm does not. Three factors of diffusion of innovation (DOI)- trialability, compatibility, and observability- positively impact attitude towards EV adoption.
 Unique Contribution to Theory, Practice and Policy: Findings from the research explain the low adoption of electric vehicles in Rwanda. They can serve as an objective basis for policymakers to upscale EV uptake in Rwanda and brings to perspective the context of Rwanda on factors of EV adoption.

Enablers of Electric Vehicles Adoption in India: A Review

India is moving towards electric vehicles. However, the road to the progress of EV adoption does not seem to be smooth and may need effort from the people and the government. With regard to the growth of Electric Vehicles in India, there is a need to find the factors that could hasten its progress. In this paper, we on the basis of the review of the relevant literature from the scientific database are suggesting a range of factors which requires the attention of policymakers and other stakeholders that could contribute to improving electric vehicle adoption in India. The factors are explained in detail along with its implication on electric vehicle adoption.

Analysis of Carbon Saving by the Adoption of Electric Vehicles in a Region Where Electricity Generation is Dominated by Thermal Power Plants

One method of reducing atmospheric CO2 emissions in the transportationsector is the replacement of conventional fossil fuel-based vehicles withElectric Vehicles (EVs). However, fossil fuels are still the primary sourceof electricity production in many regions and the utilization of EVs in suchregions increases the electricity demand because of battery charging. Thisresults in increased burning of fossil fuels by thermal power plants andtherefore can offset savings in CO2 emissions resulting from the adoptionof EVs. In this paper, we consider a scenario where all fossil fuel-basedconventional vehicles are replaced by EVs and then estimate the net CO2emission savings resulting from the adoption of EVs in a region whereelectricity is primarily supplied by thermal plants. Only emissions generatedduring the operational phase of vehicle use are considered; emissions duringthe production phase are not considered. The region under consideration is Madeira, Portugal where thermal plants account for 80% of the total electric-ity produced. Our findings suggest that although EVs have huge potential tosave CO2 emissions, a substantial amount of the savings can be offset due tothe increased burning of fossil fuels by thermal plants to meet the electricaldemand of charging batteries.

What EV users say about policy efficacy: Evidence from Shanghai

Sustainable EV adoption is critical to urban low-carbon future. The in-depth analysis of urban incentives' role in encouraging EV purchases is less examined. The perspectives of EV adopters can provide unique insights into policy implementation and effectiveness, informing future policy design and learning. Taking Shanghai—a city with roughly 4% of global EV stock—as the case, we aim to fill the above gaps via an online survey among existing EV owners. Our analysis shows that (a) urban EV strategies played a critical role in Shanghai's early adoption success, encouraging many first-time buyers to choose EVs over petrol cars, avoiding future lock-in emissions; (b) locally tailored measures such as free license plates and access to highways during rush hours significantly encouraged EV purchases; and (c) users' feedback on policy implementation reveals challenges for next-step scale adoption, especially regarding an unsupportive installation environment for private chargers, and inadequate services, e.g., infrastructure maintenance and the building up of a used-car market. These findings suggest city-level incentives can increase EV uptake but are insufficient to support a complete EV transition. Research needs to look beyond incentives for early adopters and into policy and social aspects that can support upscaling and social embedding of EVs.

A model of extended technology acceptance for behavioral intention toward EVs with gender as a moderator.

Technology has contributed significantly to the adoption of EVs (EVs) in the era of industry 4. 0. However, consumer intentions for EVs have been elusive, and the pace of adoption has been confined. Therefore, this study aims to investigate the influence of external factors in promoting customer behavioral intention for EVs. The study also investigates the mediating role of perceived ease of use (PEU) and perceived usefulness (PU) between external factors and consumer intentions for EVs. It also examined the moderating role of gender on the study variables. A study approach based on the expanded version of the technology acceptance model (TAM) was utilized to analyse data from 203 customers in China. The model was tested using structural equation model (SEM) and multigroup analysis (MGA) techniques. The results indicated that two external factors have a positive relationship with TAM constructs. The results also indicate that PEU and PU have a serial mediating relationship between external factors and behavioral intention. Finally, the study revealed gender-related differences in TAM for EVs. The study's findings help managers to design successful strategies by knowing the external factors impacting customer EV intentions and gender differences. Finally, this is a ground-breaking research that applies TAM to the automobile sector. As a result, examining both new and current factors and evaluating them in a new setting adds to the body of the literature on the adoption of technology.

Regional Electric Vehicle Fast Charging Network Design Using Common Public Data

Electric vehicles rely on public fast charging when traveling outside a single charge range. Networks of fast charging hubs are a preferred solution, but should be deployed according to a design that avoids both redundant infrastructure representing overinvestment, and “charging deserts” which limit travel by EVs and thus inhibit EV adoption. We present a two-stage design strategy for a network of charging hubs relying on common public data including maps of roadways and electrical systems, and ubiquitous and readily accessible daily traffic volume data. First, the network design is based on the electrical distribution system, roadways, and a target inter-hub driving distance. Second, the number of fast chargers necessary at each hub to support expected vehicle kilometers is determined such that queuing to charge is infrequent. A case study to prepare Nova Scotia, Canada for the 2030 electric fleet of 15% of vehicles results in a network design with an average hub catchment area of 1230 km2 and 354 electric vehicles per fast charger, and ensures that they are equitably distributed and can enable travel by EV throughout the jurisdiction.

Can distribution grid infrastructure accommodate residential electrification and electric vehicle adoption in Northern California?

In this paper we ask: in what ways will utilities need to upgrade the electric distribution grid to accommodate electrified loads, and what will those upgrades cost? Our study focuses on the PG&E service area in Northern California, which serves 4.8 million electricity customers and is subject to aggressive targets for both EV adoption and electrification of residential space and water heating. We create spatio-temporally detailed electricity demand forecasts, and compare that demand to distribution infrastructure limits across a range of technology adoption scenarios. We find that electrification of residential space and water heating will lead to fewer impacts on distribution feeder capacity than EV charging, but that both transitions will require an acceleration of the current pace of upgrades. We also find that timing and location have a strong influence on total capacity additions in important ways: for example, scenarios that favor daytime EV charging have similar impacts to those with managed nighttime residential charging, but uncontrolled nighttime residential charging could have significantly larger impacts. We project that these upgrades will add at least $1 billion and potentially over $10 billion to PG&E’s rate base. We conclude that measures that enable the completion of a high number of upcoming upgrade projects—including addressing workforce and supply chain constraints, and pursuing non-wires alternatives like energy storage and demand response—are critical to successful electrification.

Health impacts from TRAPs and carbon emissions in the projected electric vehicle growth and energy generation mix scenarios in Malaysia

Road transport contributes over 70% of air pollution in urban areas and is the second largest contributor to the total carbon dioxide emissions in Malaysia at 21% in 2016. Transport-related air pollutants (TRAPs) such as NOx, SO2, CO and particulate matter (PM) pose significant threats to the urban population's health. Malaysia has targeted to deploy 885,000 EV cars on the road by 2030 in the Low Carbon Mobility Blueprint (LCMB). This study aims to quantify the health co-benefits of electric vehicle adoption from their impacts on air quality in Malaysia. Two EV uptake projections, i.e. LCMB and Revised EV Adoption (REVA) projections, and five electricity generation mix scenarios were modelled up to 2040. We used comparative health risk assessment to estimate the potential changes in mortality and burden of diseases (BoD) from the emissions in each scenario. Intake fractions and exposure-risk functions were used to calculate the burden from respiratory diseases (PM2.5, NOx, SO2, CO), cardiovascular diseases and lung cancer (PM2.5). Results showed that along with a net reduction of carbon emissions across all scenarios, there could be reduced respiratory mortality from NOx by 10,200 mortality (176,200 DALYs) and SO2 by 2600 mortality (45,400 DALYs) per year in 2040. However, there could also be additional 719 mortality (9900 DALYs) per year from PM2.5 and 329 mortality (5600 DALYs) from CO per year. The scale of reduction in mortality and BoD from NOx and SO2 are significantly larger than the scale of increase from PM2.5 and CO, indicating potential net positive health impacts from the EV adoption in the scenarios. The health cost savings from the reduced BoD of respiratory mortality could reach up to RM 7.5 billion per year in 2040. In conclusion, EV is a way forward in promoting a healthy and sustainable future transport in Malaysia.

Identifying and Mitigating the Barriers for Vehicle-to-Grid Adoption in India

This study gauges the current scenario of EVs in India as a precursor to the adoption of V2G on a large scale. It outlines the barriers to complete EV adoption under three challenge categories. It discusses the motivation for the use of vehicle-to-grid by describing the technology in detail and discussing an overview of how it works. Lastly, the study outlines how popular optimization techniques have been employed to solve individual optimization and scheduling tasks to optimize power, cost, and emissions for V2G.

Analysis of Consumers’ Electric Vehicle Purchase Intentions: An Expansion of the Theory of Planned Behavior

For the purpose of paving the way for reducing environmental pollution globally, adapting green energy to people’s lives in more areas is seen as a good solution. The strategic plan implemented to prevent possible energy and water shortages in the future includes cleaning the environment and air from carbon emissions as soon as possible. Countries are taking mandatory sectoral and individual measures to remove the use of CO2-based fuels. As a part of the sustainable development process for Turkey, which is trying to convince its individuals to use more green energy, it is important for society to adopt more electric vehicles. However, there are few internationally accepted studies on the adoption of EVs in Turkey, and a limited number of studies include individuals’ environmental concerns (EC) and green trust (GT) structures. In this research, which we started on the basis of filling this literature gap by taking behavioral factors into account, we expand the TPB framework (subjective norm (SN), attitude (AT), and perceived behavioral control (PBC)) with the “EC” and “GT” constructs. So, with this research, we examine the behavioral factors that affect the intention to purchase electric vehicles (EVPI) of consumers residing in Turkey, based on the theory of planned behavior. Thus, we aim to reveal the barriers to the adoption of EVs in Turkey with an empirical application and SEM analysis. The first phase includes a review of the literature, adaptation of the survey, and development of the hypotheses. The second phase involves conducting a survey with 626 consumers whose information was obtained from four dealers in Turkey. We used Cronbach’s alpha and CFA analyses on the data obtained from the survey. In the final phase, we performed an SEM analysis for our extended theory of planned behavior (ETPB) and hypotheses. The CFA results revealed that the survey showed compatibility with EV purchase intentions. The SEM results indicated that the behavioral constructs of AT, PBC, EC, and GT were positively correlated with EV purchase intentions, and our new ETPB model, extended with EC and GT, was suitable for predicting consumers’ EVPI, suggesting that EVPI are a result of behavioral constructs. This study is unique for being the first in Turkey to focus on whether the factors of EC or GT can predict consumers’ EVPI. On the other hand, it was found that SN had a negative effect on consumers’ EVPI, and this result was in agreement with some studies in the literature and contradicted by others. In addition, we make suggestions based on the findings of the research to the country and related sector managers in order for the country to progress at a level that will set an example for other developing countries in its sustainable development plan. This study contributes to the EVs industry by revealing the consumers’ responses and increasing their marketing efforts. Our findings constitute a comprehensive example for further research on sustainable consumption, EVs, EVPI, and ETPB.

The purchase intention of electric vehicles in Hong Kong, a high-density Asian context, and main differences from a Nordic context

In this paper, we aim to examine people's EV purchase intention in Hong Kong, an Asian compact city, and how the influential factors are different from the Western context, for which a low-density Nordic context, Denmark, was chosen. To achieve this, we conducted a survey in Hong Kong to understand the effects of several key factors, including subjective norms, personal norms, and perceptions and knowledge about EVs. Structural equation modelling was employed and multi-group analysis was conducted. Our findings show that EV purchase intentions in Hong Kong are highly value-driven with the assimilation to social expectations directly and strongly encouraging individuals' EV acceptance, which is different from the European case where the adoption desire is built upon the assessment of usage difficulty. In addition, range anxiety poses a direct deterrence to EV adoption even in the compact city. Availability of charging opportunities, be it the public ones or home-based ones, plays a critical role in an individual's decision of EV adoption in the high-density city. Our study reveals a strong disparity in the pathways towards EV adoption between the Asian and the Nordic contexts, thereby illustrating the necessity to differentiate e-mobility promotion policies in compact cities from low-density cities.

A Study on Barriers to Adoption of Electric Vehicles

Adoption of green& sustainable technologies in the transport sector is the need of the hour. High initial price charging time & limited range are the obstacles towards the adoption and diffusion of electronic vehicles. Deployment of electronic vehicle has been a key measurers to reduce pollution in urban areas caused by the logistic sector. A technology emerged more than a century ago EV failed in its several encounters with the gas powered cars and the efforts to penetrate the market. Though much progress has been made in the past decade, the wide adoption of EVs is still in question. In the process of reducing the pollutions world is searching for every alternative to reduce the emissions and find the solutions to the alternative energy’s. The study aims to find out those barriers to the adoption of electric vehicles. The articles is contemporary and examines the different factors that affect a consumer’s adoption of an EV.