Electric Vehicle Infrastructure Research Articles

A Review on the Renewable Sources Based Microgrid for Electric Vehicle Charging using various Emerging Technologies

Abstract: This review examines the integration of renewable energy sources into microgrids for electric vehicle (EV) charging, leveraging emerging technologies such as the fuzzy logic and genetic algorithm. It addresses the challenges of scaling EV infrastructure, focusing on the potential of solar, wind, and bio-energy to enhance sustainability and grid independence. The paper discusses how fuzzy logic, genetic algorithm optimize energy management and maintenance. Overall, the study advocates for a holistic approach to develop efficient, resilient, and sustainable EV charging systems through the synergistic use of renewable microgrids and advanced technologies.

Electrifying the road: Navigating the transition to electric vehicles in Connecticut through hybrid insights and fleet evolution

The adoption of light duty electric vehicles (EVs) in the past 5 years has accelerated dramatically. As EVs continue penetrating the U.S. market, it is critical to understand what a sustainable transition within the transportation sector will look like in relation to mitigating impacts of climate change. This work aims to fill two existing gaps in the current literature: 1) investigate the positive and negative potential influences of the emerging EV transition within the U.S. market and 2) investigate the types of vehicles EVs are replacing. We fulfill these objectives by utilizing a unique attribute dataset of all vehicles in Connecticut (USA) on the road between 2013 and 2020. Our findings suggest that the penetration rate of traditional hybrid vehicles (e.g., Toyota Prius) is an important predictor of EV adoption. Furthermore, our results show that in Connecticut most of that transition is occurring among hatchbacks (e.g., Chevrolet Bolt), a body style where internal combustion engine (ICE) versions have relatively high fuel efficiencies compared with other major vehicle types (e.g., pickup trucks or SUVs). Our results offer important implications for policymakers in terms of maximizing the deployment of EVs and EV infrastructure and the path in which the automotive sector is progressing towards decarbonization.

Equitable charging infrastructure for electric vehicles: Access and experience

Equitable charging infrastructure for electric vehicles: Access and experience

Progress, Challenges and Opportunities of Electromobility in Mexico

This paper highlights the attempts made by the government to integrate electromobility in Mexico, despite not having a well-defined National Electric Mobility Strategy, and compares the advances, challenges and future opportunities of electromobility with other countries with similar conditions in terms of the public policy, the evolution of the electric vehicles market, the charging infrastructure, incentives and legal framework, and diffusion channels. The results showed that Mexico has made partial advances in the infrastructure, production and exportation of electric vehicles, consumer incentives and project implementation. However, the country requires strengthening strategies on the economic incentives for the user and industry, homologation of chargers, training of personnel specialised in electric vehicles, handling and destination of batteries, and defining its National Electric Mobility Strategy. As a way forward, our study suggests comparing the electromobility strategies of other countries and understanding the key aspects that might enable the successful introduction of electric vehicles.

OCPP Interoperability: A Unified Future of Charging

Electric vehicle (EV) adoption grows steadily on a global scale, yet there is no consistent experience for EV drivers to charge their vehicles, which hinders the important EV mass market adoption. The Open Charge Point Protocol (OCPP) is the solution to this challenge, as it provides standardization and open communication between EV infrastructure components. The interplay of the OCPP with open cross-functional communication standards boosters driver experience on the one hand, while the charging station itself is integrated into a renewable energy ecosystem. This paper presents a deep dive into the combination of the OCPP with the OpenADR protocol, the Open Smart Charging Protocol (OSCP), the ISO 15118, and eRoaming protocols to explore possibilities and limitations. Furthermore, we suggest LoRa communication as an alternative to IP-based communication for deep-in building applications. Hence, this paper reveals the next important steps towards a successful EV mass market transition powered by user-friendliness and green energy.

Intelligent Integration: Harnessing Artificial Intelligence for Enhanced Performance and Efficiency in Electric Vehicles

The transition towards electric vehicles (EVs) necessitates the development of efficient and reliable charging infrastructure. This paper presents an AI-driven approach to optimize EV infrastructure, focusing on five key aspects: profiling, augmentation, forecasting, explainability, and charging efficiency. Profiling involves understanding EV drivers' behaviors and preferences, facilitating targeted infrastructure development. Augmentation utilizes AI algorithms to identify optimal locations for new charging stations or upgrades based on usage patterns and demand forecasts. Forecasting models leverage machine learning techniques to predict future EV adoption rates and charging demands, aiding in infrastructure planning. These datasets can be used to generate insights and decisions through the use of artificial intelligence (AI) algorithms. A thorough analysis of the usefulness of AI in charge-demand profiling, data augmentation, demand forecasting, demand explainability, and charge optimization of the EVI has not yet been conducted, despite a number of recent studies in this area. This study's goal was to create, develop, and assess a thorough AI framework that fills in this EVI gap. The findings of an empirical assessment of this AI framework on an actual EVI case study validate its usefulness in tackling the new issues surrounding dispersed energy resources in the deployment of EVs.

Research of an autonomous power source for elec-tric vehicles and their charging infrastructure

Research of an autonomous power source for elec-tric vehicles and their charging infrastructure

The Current State of the National Electric Vehicle Infrastructure Program Funding

Reducing the transportation sector's greenhouse gas (GHG) emissions by transitioning away from fossil fuels and its impact on communities and the environment continues to receive considerable attention. In 2022, the U.S. transportation sector was responsible for generating the largest share of the United States' GHG emissions at approximately 37 percent of total emissions.1 Electric vehicles (EVs) represent a viable option that can contribute significantly to reducing transportation sector emissions. As EVs become increasingly prevalent, ensuring the availability of adequate charging infrastructure to support these vehicles is a top priority of the Biden Administration and many states.

A Hybrid Deep Learning Model Utilizing Cross-Structural Multi-Behavioral Comparative Recommendation for Sustainable Electric Transportation Infrastructure

Ensuring the sustainability of transportation infrastructure for electric vehicles (e-trans) is increasingly imperative in the pursuit of decarbonization goals and addressing the pressing energy shortage. By prioritizing the development and maintenance of resilient e-trans platforms through the optimization of the public charging network, electric vehicle businesses can effectively meet the needs of users, thereby contributing to efforts aimed at improving environmental quality. To achieve this goal, researching the dynamics of vehicle user behaviors plays a crucial role. In this paper, we propose cross-structure multi-behavior contrastive learning for recommendation (C-MBR), which takes into account the dynamic preferences of users, and develops model profiles from the global structure module, local structure module, cross-behavior contrastive learning module, cross-structure contrastive learning module, and model prediction and optimization. C-MBR is mainly designed to learn user preferences from the diversity of users’ behaviors in the process of interacting with the project, so as to grasp the different behavioral intentions of users. The experimental and analytical research is further conducted and validated for dealing with cold start problems. The results indicate that C-MBR has a strong ability to deal with the problem of sparse data. Compared with the ablation experiment, the model performance of C-MBR is significantly enhanced, showing that the C-MBR model can fully apply the information of a global structure and local structure in cross-structure comparative learning and multi-behavioral comparative learning to further alleviate the problem of data sparsity. As a result, the e-trans infrastructure will be significantly enhanced by addressing the issue of data-driven disruption.

Ukraine’s post-war recovery program as a basis for the development of electric vehicles and electric infrastructure

The article is devoted to the determination of the development of domestic electric vehicle transport and electric vehicle infrastructure on the basis of such an economic and legal instrument as the post-war recovery program of Ukraine, taking into account EU approaches in the legal regulation of decarbonization of the transport sector. The European Commission adopted the Communiqué to the European Parliament, the European Council, the European Economic and Social Committee and the Committee of the Regions «Assistance and Reconstruction of Ukraine» on 18.05.2022, where the provision of funds for the post-war reconstruction of Ukraine is conditioned by our country’s compliance with current European policies and standards, one of which there is decarbonization. Therefore, Ukraine should carry out post-war reconstruction taking into account the experience and approaches outlined by the international acts of the EU. The National Council for the Recovery of Ukraine from the Consequences of the War, a consultative and advisory body under the President of Ukraine, proposed a draft Plan for the Recovery of Ukraine. Based on the analysis of the provisions of the project component of the Recovery Plan of Ukraine «Restoration and development of infrastructure». It was concluded that the project of the Recovery Plan of Ukraine and its component «Recovery and development of infrastructure» is an economic and legal instrument of a programmatic nature. It establishes a systematic approach to the more active use of electric vehicles and the development of electric charging stations. The plan defines short-term, medium-term and strategic tasks for the development of electric mobility infrastructure. The general program approaches defined in this act correspond to the directions established by the normative legal acts that were adopted to regulate the issues of environmentalization of the domestic transport sector before the war, as well as the general directions of the development of the charging infrastructure of electric vehicles, outlined by the international acts adopted in the EU. The disadvantage is that a complete transition to electric transport for the transportation of passengers on urban and suburban routes is foreseen in the medium term, which is an extremely limited period. In the Plan, it is expedient to use the objective indicators of the development of the system of electric filling stations, which are established in the domestic regulatory and technical acts. Also, the directions of the development of electric transport and the network of electric gas stations should be reflected in the programs of comprehensive restoration of the region, the territory of the territorial community.

Suitable law-based location selection of high-power electric vehicles charging stations on the TEN-T core network for sustainability: a case of Poland

With the upcoming implementation of the amendment to Regulation (EU) 2019/631 of the European Parliament and of the Council, from 2035 there will be a ban on the registration of new vehicles with internal combustion engines (ICE) in the Member States of the European Union (EU). Consequently, changes in the transportation sector, resulting from the increasing use of electric vehicles, appear to be inevitable. According to the adopted legal acts, the European Union Member States will be obliged to develop, among others, a charging infrastructure and access to public charging stations for electric vehicles. As a result, there will be a need to ensure a significant increase in the power and the number of charging stations and to determine their appropriate location. The article presents the challenges faced by charging station operators and difficulties related to the further development of electric vehicle charging infrastructure in Poland. The still poorly developed public charging infrastructure for electric vehicles, especially in service areas located along the main communication routes, remains the main obstacle to the development of electromobility. In the context of legal, financial, technological, and organizational challenges, the problem of the proper distribution of electric vehicle charging stations along the main communication routes is therefore of particular importance. The aim of the article is to present a new, proprietary method for determining the location of electric vehicle charging stations in Poland within the Trans-European Transport Network (TEN-T), which considers objective location factors: adherence to AFIR requirements, the specificity of the Polish power system and existing parking infrastructure. As a result of using the developed method, a list of 188 recommended locations for the construction of electric vehicle charging stations in Poland along the Trans-European Transport Network (TEN-T) was created. It has been shown in this way that the use of the presented method enables the suitable determination of the location of electric vehicle charging stations along transport routes, considering legal, financial, and technological requirements, which will significantly facilitate the operation of zero-emission transport.

Dynamic charging as a complementary approach in modern EV charging infrastructure

Whether the future of transportation is going to be electric or not is no longer a question. Electric vehicles (EVs) offer several benefits toward global sustainability. However, without a variety of charging infrastructures that cover diverse forthcoming charging needs, the speed of vehicle electrification may be slow and limited. In this study, we investigate the synergistic benefits of traditional charging stations and an emerging alternative, i.e., wireless dynamic charging roads, focusing on their impact on the daily commute of EV users. We center our evaluation on quantifiable metrics, chiefly time and convenience, and deploy computer simulations utilizing authentic transportation datasets from New York City, USA. Our findings underscore that integrating both charging stations and charging roads can substantially alleviate detours for EV users and remarkably reduce additional charging time. Our research provides evidence to encourage researchers, EV manufacturers, urban infrastructure planners, and policymakers to explore future charging infrastructures for EVs, with a notable emphasis on wireless dynamic charging roads.

Rush to Charge, Dead to Drive: Application of Deadline Rush Model to Electric Vehicle User's Charging Behavior.

This work aims to estimate the portion of electric vehicle (EV) users who exhibit procrastination-like behavior, almost equivalent to an "empty" battery, before they decide to charge their vehicles. There is a human tendency to procrastinate when a deadline approaches. Human behavior in the presence of deadlines has been studied in different fields to evaluate individuals' performance or organizational efficiency and effectiveness. However, this phenomenon has not been investigated among EV users. This study explores users' procrastination-like behavior among 69 Rhode Island public charging stations' data representing 70,611 charging events. The Deadline Rush Model is incorporated to model frequent users' charging profiles. To conduct a robust estimation, the Bayesian Mixture Model is implemented. With the selection of an informative prior, the Bayesian Mixture Model estimated that almost one-third of frequent users procrastinate charging. The majority of procrastination-like users have small battery sizes. Although procrastination-like users need to charge when they arrive at a location, that might not necessarily be true for a plug-in hybrid; thus, systematically, they can clog the system for other users whose needs are more pressing. Understanding unique and unexplored charging behaviors among EV users is beneficial to EV infrastructure stakeholders in reducing the adoption threshold by providing a reliable and ubiquitous charging network. The findings identify a different kind of demand on the EV infrastructure than previously modeled and can directly influence future decision-making criteria in terms of planning to optimize to accommodate EV drivers with different charging behaviors.

Planning a Sustainable Electric Vehicle Infrastructure Considering Battery Life: Modeling and Resolution by the Multi-agent Q-learning Metaheuristic

Planning a Sustainable Electric Vehicle Infrastructure Considering Battery Life: Modeling and Resolution by the Multi-agent Q-learning Metaheuristic

A Study of Select Variables Impacting Buying Behaviour of Electric Cars In India

The automobile industry is currently undergoing a significant transformation in its approach to transportation, primarily driven by increased awareness of climate change and limited resources. The recent resurgence of electric vehicles in the market can be attributed to various factors, including advancements in battery technology and government policies aimed at reducing vehicle emissions. This research focused on examining the factors that influence consumer purchasing behavior regarding electric cars in India. Primary data was collected through a self-administered questionnaire distributed to consumers. The survey sample was selected using a combination of conventional and snowball sampling techniques, drawing participants from the target population. The study and survey took place in the Delhi/NCR region from January to February 2023. A total of 649 questionnaires were distributed, out of which 324 were returned. After analysing the data, 214 fully completed responses were used for further analysis. The findings indicated that financial barriers, concerns about vehicle performance, lack of charging infrastructure, environmental awareness, societal influence, and knowledge of electric vehicles all significantly impact the decision-making process when considering the purchase of electric vehicles.

Scenario Planning of Pertamina Patra Niaga Business Strategy to Address the Growth of the Indonesian Electric Vehicle Market

PT Pertamina Patra Niaga is facing an era of energy transition, and one of the biggest phenomena is the adoption of electric vehicles (EVs). Massive EV adoption will impact Patra Niaga’s future business, and they must prepare a strategy to deal with these changes. This research aims to determine the factors that influence EV adoption in Indonesia and propose strategies that need to be carried out by Patra Niaga. The literature review shows that internal and external factors are very influential in determining Patra Niaga’s strategy. The research design is qualitative, with data obtained from primary sources from interviews and secondary data sources, including industry documents, reports, and journals. Using the scenario planning method with the PESTEL approach, the paper identifies four possible scenarios for the future of EV adoption in Indonesia. The possible scenarios are green tech frontier, policy-driven change, market-led innovation, and stagnant development. Environment analysis conducted both external analysis and internal analysis. The research uses Porter’s Five Forces to identify rivalry among the industry players for external analysis. Meanwhile, the internal analysis uses the use VRIO Framework to identify the competitive advantage of the company and the strength and weakness analysis to determine the opportunities and threats for the company. Finally, the research uses the BCG Matrix to develop a strategy for each scenario. Based on the BCG Matrix, the proposed strategies are to invest more in the EV infrastructure where the scenario is green tech frontier, to invest or divest where the scenario is policy-driven, to keep the EV infrastructure business running where the scenario is market-led innovation, and to s liquidated where the scenario is stagnant development. The chosen strategy is suggested to be implemented based on the probability of occurrence for each of the scenarios within a timeframe from the year 2024 to 2035 by involving various divisions in the company, including marketing, business development, and project leader of the EV division.

Modeling the Impact of Different Policies on Electric Vehicle Adoption: An Investigative Study

Electric Vehicles (EVs) emerge as a crucial solution for alleviating the environmental footprint of the transportation sector. However, fostering their widespread adoption demands effective, targeted policies. This study introduces a versatile model, amalgamating stakeholders and policies and leveraging local data with broader market applicability. It delineates two key EV adopter groups—innovators and imitators—shedding light on their evolving impact on adoption trends. A pivotal feature of the model is the factoring of EV attractiveness, comprising Life-Cycle Cost (LCC), Driving Range, Charging Time, and infrastructure availability, all of which are expected to improve with the fast technological advancement of EVs. Financial policies, notably subsidies, prove potent in boosting EV adoption but fall short of targeted sales due to imitator lag. In response, a pragmatic solution is proposed: a government-led EV acquisition of 840 EVs, coupled with a 20% subsidy on new EV purchases and a 20% tax on new ICEV purchases, potentially realizing a 30% EV sales target by 2035. Future research avenues may delve into behavioral dynamics prompting imitators’ adoption, optimizing EV infrastructure strategies, and assessing the socio-economic impacts of EVs. Interdisciplinary approaches hold promise for enriched insights for effective EV integration policies.

Sustainable transportation in developing countries: uncovering factors influencing electric vehicle purchase intention in India

ABSTRACT This study examines the factors that impact the purchase intention of electric vehicles (EVs) in emerging economies like India. By employing the Push, Pull, and Mooring (PPM) theory, this study contributes to the existing literature by shedding light on the factors influencing purchase intention of EVs. In the first stage of the study, twitter text mining was conducted to extract the main topics discussed about EVs. The second stage involved a focus group discussion to condense the identified topics into key factors influencing the purchase intention of EVs. Finally, choice-based conjoint analysis was employed in the third phase to comprehend the utility and prioritize the identified factors. Additionally, topic modelling can be valuable for marketing managers, product managers, and branding specialists in developing a brand image and positioning for EVs. Furthermore, the findings of this study can assist policymakers in creating regulatory frameworks to support the development of EV infrastructure.

The Impact of Government Incentives on Electric Vehicle Adoption in the Metropolitan Jakarta Area

This study investigates the effect of government economic incentives on electric vehicles (EV) in the metropolitan Jakarta area (Jakarta, Bogor, Depok, Tangerang, Bekasi). A survey was collected from 121 prospective and current EV users in Jakarta and its neighboring regions area. The collection was then analyzed using logistic regression. The research finds that EV subsidy, EV infrastructure, EV tax deduction, and age have significant effects on EV adoption. According to this stance, higher EV subsidy propels more EV adoption. In addition, respondents significantly consider the availability of EV infrastructure for EV adoption. Our study also reveals that the younger the age, the higher the preference for EV adoption. Furthermore, the lower the tax deduction, the increasing adoption of electric vehicles. Those variables are important factors to amplify EV adoption among our research respondents. This study implies that potential consumers are aware of and react positively to policy efforts to reduce upfront and maintenance costs for the transition to EV cars in the metropolitan Jakarta area.

Charging Stations for Large-Scale Deployment of Electric Vehicles

The large-scale adoption of electric vehicles will require a charging infrastructure that meets the new needs that will arise. Currently, the charging infrastructure for electric vehicles is still in the early stages of development, not least because of the low number of electric vehicles in use. However, there are still many questions to be answered when it comes to standardization in terms of connectors, DC or AC charging, and power, as well as both operational and economic issues. Although this topic has been the subject of numerous studies over the last ten years, there are still gaps to be filled, particularly with regard to the mix of different recharging strategies (normal, accelerated, fast, induction-track, etc.), as well as the economic and operational aspects. Moreover, the relationship between users and private cars is changing rapidly, and charging behaviors are not yet well established.