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With the need for more environmentally friendly transportation and the wide deployment of electric and plug-in hybrid vehicles, electric vehicle (EV) charging stations have become a major issue for car manufacturers and a real challenge for researchers all over the world. Indeed, the high cost of battery energy storage, the limited EV autonomy and battery lifespan, the battery charging time, the deployment cost of a fast charging infrastructure, and the significant impact on the power grid are the origin of several research projects focused on advanced power electronics topologies and the optimization of the EV charging stations in terms of power transfer and geographical location. Three charging levels can be distinguished, which differ in terms of output power and charging time. The higher the level of charging, the faster the charging process, as more power is delivered to the vehicle at the expense of power quality issues and disturbances. Moreover, three types of charging systems can be distinguished, which are inductive recharging (contactless power transfer), conductive charging systems, and battery swapping. Additionally, EVs encompass fuel cell (FC) EVs, which uses hydrogen as primary energy resources, which is nowadays under extensive research activities in academia and industry. This review paper aims at presenting a state of the art review of major advances in power electronics architectures for EVs traction drives, and battery-based EVs charging stations. Specifically, the focus is made on light-duty electric vehicles drivetrain power electronics and charging stations specifications, the proposed power electronics solutions, the advantages and drawbacks of all these technologies, and perspectives for future research works in terms of smart EV charging and up-to-date solutions for power system disturbances mitigation.

The electric vehicle offers many promises-increasing U.S. energy security by reducing petroleum dependence, contributing to climate-change initiatives by decreasing greenhouse gas (GHG) emissions, stimulating long-term economic growth through the development of new technologies and industries, and improving public health by improving local air quality. There are, however, substantial technical, social, and economic barriers to widespread adoption of electric vehicles, including vehicle cost, small driving range, long charging times, and the need for a charging infrastructure. In addition, people are unfamiliar with electric vehicles, are uncertain about their costs and benefits, and have diverse needs that current electric vehicles might not meet. Although a person might derive some personal benefits from ownership, the costs of achieving the social benefits, such as reduced GHG emissions, are borne largely by the people who purchase the vehicles. Given the recognized barriers to electric-vehicle adoption, Congress asked the Department of Energy (DOE) to commission a study by the National Academies to address market barriers that are slowing the purchase of electric vehicles and hindering the deployment of supporting infrastructure. As a result of the request, the National Research Council (NRC)-a part of the National Academies-appointed the Committee on Overcoming Barriers to Electric-Vehicle Deployment. This committee documented their findings in two reports-a short interim report focused on near-term options, and a final comprehensive report. Overcoming Barriers to Electric-Vehicle Deployment fulfills the request for the short interim report that addresses specifically the following issues: infrastructure needs for electric vehicles, barriers to deploying the infrastructure, and possible roles of the federal government in overcoming the barriers. This report also includes an initial discussion of the pros and cons of the possible roles. This interim report does not address the committee's full statement of task and does not offer any recommendations because the committee is still in its early stages of data-gathering. The committee will continue to gather and review information and conduct analyses through late spring 2014 and will issue its final report in late summer 2014. Overcoming Barriers to Electric-Vehicle Deployment focuses on the light-duty vehicle sector in the United States and restricts its discussion of electric vehicles to plug-in electric vehicles (PEVs), which include battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). The common feature of these vehicles is that their batteries are charged by being plugged into the electric grid. BEVs differ from PHEVs because they operate solely on electricity stored in a battery (that is, there is no other power source); PHEVs have internal combustion engines that can supplement the electric power train. Although this report considers PEVs generally, the committee recognizes that there are fundamental differences between PHEVs and BEVs.

Present trends indicate that electrical vehicles (EVs) are favourable technology for road network transportation. The lack of easily accessible charging stations will be a negative growth driver for EV adoption. Consequently, the charging station placement and scheduling of charging activity have gained momentum among researchers all over the world. Different planning and scheduling models have been proposed in the literature. Each model is unique and has both advantages and disadvantages. Moreover, the performance of the models also varies and is location specific. A model suitable for a developing country may not be appropriate for a developed country and vice versa. This paper provides a classification and overview of charging station placement and charging activity scheduling as well as the global scenario of charging infrastructure planning. Further, this work provides the challenges and solutions to the EV charging infrastructure demand and deployment. The recommendations and future scope of EV charging infrastructure are also highlighted in this paper.

The transportation sector of the world is in the transformation stage, shifting from conventional fossil fuel-powered vehicles to zero or ultra-low tailpipe emission vehicles. To support this transformation, a proper charging station (CS) infrastructure in combination with information technology, smart distributed energy generating units, and favorable government policies are required. The motive of this paper is to address the key aspects to be taken care of while planning for the charging station infrastructure for electric vehicles. The paper also provides major indagation and developments in planning and technological aspects that are going on for the enhancement of the design and efficient management of charging station infrastructure. The paper addresses the present scenario of India related to electric vehicle charging station developments. The paper specially provides a critical review on the research and developments in the charging station infrastructure, the problems associated with it, and the efforts that are going on for its standardization to help the researchers address the problems.

In the past few years, interest in plug-in electric vehicles (PEVs) has grown. Advances in battery and other technologies, new federal standards for carbon-dioxide emissions and fuel economy, state zero-emission-vehicle requirements, and the current administration's goal of putting millions of alternative-fuel vehicles on the road have all highlighted PEVs as a transportation alternative. Consumers are also beginning to recognize the advantages of PEVs over conventional vehicles, such as lower operating costs, smoother operation, and better acceleration; the ability to fuel up at home; and zero tailpipe emissions when the vehicle operates solely on its battery. There are, however, barriers to PEV deployment, including the vehicle cost, the short all-electric driving range, the long battery charging time, uncertainties about battery life, the few choices of vehicle models, and the need for a charging infrastructure to support PEVs. What should industry do to improve the performance of PEVs and make them more attractive to consumers? At the request of Congress, Overcoming Barriers to Deployment of Plug-in Electric Vehicles identifies barriers to the introduction of electric vehicles and recommends ways to mitigate these barriers. This report examines the characteristics and capabilities of electric vehicle technologies, such as cost, performance, range, safety, and durability, and assesses how these factors might create barriers to widespread deployment. Overcoming Barriers to Deployment of Plug-in Electric Vehicles provides an overview of the current status of PEVs and makes recommendations to spur the industry and increase the attractiveness of this promising technology for consumers. Through consideration of consumer behaviors, tax incentives, business models, incentive programs, and infrastructure needs, this book studies the state of the industry and makes recommendations to further its development and acceptance.

Electric vehicles (EVs) are considered as the leading-edge form of mobility. However, the integration of electric vehicles with charging stations is a contentious issue. Managing the available grid power and bus voltage regulation is addressed through renewable energy. This work proposes a grid-connected photovoltaic (PV)-powered EV charging station with converter control technique. The controller unit is interfaced with the renewable energy source, bidirectional converter, and local energy storage unit (ESU). The bidirectional converter provides a regulated output with a fuzzy logic controller (FLC) during charging and discharging. The fuzzy control is implemented to maintain a decentralized power distribution between the microgrid DC-link and ESU. The PV coupled to the DC microgrid of the charging station is variable in nature. Hence, the microgrid-based charging is examined under a range of realistic scenarios, including low, total PV power output and different state of charge (SOC) levels of ESU. In order to accomplish the effective charging of EV, a decentralized energy management system is created to control the energy flow among the PV system, the battery, and the grid. The proposed controller’s effectiveness is validated using a simulation have been analyzed using MATLAB under various microgrid situations. Additionally, the experimental results are validated under various modes of operation.

Charging station (CS) planning for electric vehicles (EVs) for a region has become an important concern for urban planners and the public alike to improve the adoption of EVs. Two major problems comprising this research area are: (i) the EV charging station placement (EVCSP) problem, and (ii) the CS need estimation problem for a region. In this work, different explainable solutions based on machine learning (ML) and simulation were investigated by incorporating quantitative and qualitative metrics. The solutions were compared with traditional approaches using a real CS area of Austin and a greenfield area of Bengaluru. For EVCSP, a different class of clustering solutions, i.e., mean-based, density-based, spectrum- or eigenvalues-based, and Gaussian distribution were evaluated. Different perspectives, such as the urban planner perspective, i.e., the clustering efficiency, and the EV owner perspective, i.e., an acceptable distance to the nearest CS, were considered. For the CS need estimation, ML solutions based on quadratic regression and simulations were evaluated. Using our CS planning methods urban planners can make better CS placement decisions and can estimate CS needs for the present and the future.

Concerns over fossil fuel depletion, fluctuating fuel prices, and CO2 emissions have accelerated the development of electric vehicle (EV) technologies. This article reviews advancements in EV fast charging technology and explores the development of battery-assisted DC fast charging stations to address the limitations of traditional chargers. Our proposed approach integrates battery storage, allowing chargers to operate independently of the electric grid by storing electrical energy during off-peak hours and releasing it during peak times. This reduces dependence on grid power and enhances grid stability. Moreover, the transformer-less, modular design of the proposed solution offers greater flexibility, scalability, and reduced installation costs. Additionally, the use of smart energy management systems, incorporating artificial intelligence and machine learning techniques to dynamically adjust charging rates, will be discussed to optimize efficiency and cost-effectiveness.

To solve the problem of layout design of charging stations in the early stage of the electric vehicle industry, the user’s satisfaction and the charging convenience are considered. An electric vehicle charging station site-selection model is established based on the kernel density analysis of the urban population. The goal of this model is maximum electric vehicle user satisfaction and the highest charging convenience. Then, according to model characteristics, the immune algorithm is designed and optimized to solve the model. The optimization of the immune algorithm includes two aspects. On the one aspect, judging that the stop condition is added in the mutation link. On the other aspect, two mutation operators are designed in the optimized immune algorithm. Finally, the simulation example is determined by a three-step method in Jinan City. The results show that the electric vehicle charging station site-selection model in this paper can better meet user needs compared with traditional models. Compared with the traditional immune algorithm, the convergence speed of the optimized immune algorithm is improved, and the proposed algorithm is superior to the traditional immune algorithm in terms of stability and accuracy.

At present, the electric vehicle (EV) market is developing strongly and widely across many countries around the world. Increasing clean energy infrastructure for EVs is a possible solution to reduce greenhouse gas emissions and help improve air quality in urban areas. Electric vehicles charged by electricity from photovoltaic (PV) systems can produce less emissions than conventional EVs charged by the utility grid. Thus, the combination of solar power and EV charging stations is one of the possible methods to achieve sustainable development in the current EV market. EVs in cities in Vietnam have developed very quickly in recent times, but the charging station infrastructure is still very limited, and most existing charging stations use electricity from the utility grid. In this paper, the optimal configuration of PV-powered EV charging stations is analyzed technically and economically under different solar irradiation conditions in Vietnam. The study results show that the optimal configuration and investment efficiency of PV-powered EV charging stations in each urban area are greatly affected by the solar irradiation value and feed-in tariff (FIT) price of rooftop solar power. In Vietnam, a region with high solar irradiation, such as Ho Chi Minh, is more likely to invest in PV-powered EV charging stations than other areas with lower solar irradiation, such as Hanoi.