Relevant bibliographies by topics / Electric vehicle charging station

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Electric vehicle charging station'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Electric vehicle charging station"

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El-fedany, Ibrahim, Driss Kiouach, and Rachid Alaoui. "System architecture to select the charging station by optimizing the travel time considering the destination of electric vehicle drivers in smart cities." Bulletin of Electrical Engineering and Informatics 9, no. 1 (February 1, 2020): 273–83. http://dx.doi.org/10.11591/eei.v9i1.1564.

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The main limitations of electric vehicles are the limited scope of the battery and their relatively long charging times. This may cause discomfort to drivers of electric vehicles due to a long waiting period at the service of the charging station, during their trips. In this paper, we suggest a model system based on argorithms, allowing the management of charging plans of electric vehicles to travel on the road to their destination in order to minimize the duration of the drivers' journey. The proposed system decision to select the charging station, during advance reservation of electric vehicles, take into account the time of arrival of electric vehicles at charging stations, the expected charging time at charging stations, the local status of the charging stations in real time, and the amount of energy sufficient for the electric vehicle to arrive at the selected charging station. Furthermore, the system periodically updates the electric vehicule reservations to adjust their recharge plans, when they reach their selected earlier station compared to other vehicules requesting new reservations, or they may not arrive as they were forecast, due to traffic jams on the road or certain reluctance on the part of the driver.
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Ye, Bo, Zhang Zhou He, Guo Meng Huang, Xue Song He, and Hui Quan Li. "The Study and Design of Electric System for Photovoltaic Generation Mix Charging Station." Applied Mechanics and Materials 291-294 (February 2013): 2362–65. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2362.

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With the development of electric vehicle industry, it is necessary to construct more electric vehicle charging stations to promote the popularization of electric vehicles. As photovoltaic generation owns flexible installing, convenient power supplying, and environmental protecting characteristics, it is suitable for providing power for electric vehicle charging stations and reducing a network loads. After analyzed electric vehicle charging demand, this paper proposed the designing concept of the electric system for the photovoltaic generation mix charging station, which was based on the battery charging and discharging characteristics as well as its usage. Then, the paper provided a selection of electric equipments for the charging station and an electric wiring diagram after designing the electric system. This study and design may help for promoting construction of electric vehicle charging stations, and development and popularization of electric vehicles.
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Khobragade, Priya A. "Multiport Converter based EV Charging Station with PV and Battery." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 14, 2021): 2518–21. http://dx.doi.org/10.22214/ijraset.2021.34679.

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: As a ecofriendly electrical vehicle, is vehicles that are used electric motor or traction motor. Are receiving widespread attention around the world due to their improved performance and zero carbon emission . The electric vehicle depend on photovoltaic and battery energy storage system . Electric vehicles include not limited road and railways. It consist of many electric appliances for use in domestic and industrial purposes that is electric car ,electric bike ,electric truck ,electric trolley bus , electric air craft ,electric space craft.The main Moto of this paper is a modelling of proposed system smart charging for electrical vehicle insuring minimum stress on power grid . The large scale development of electrical vehicle we need electric charging station for example fast charging station and super-fast charging station . During a peak demand load , large load on charging station due to the voltage sag , line fault and stress on power grid . At this all problem avoid by multiport converter based EV charging station with PV and BES by using analysis of MATLAB simulation. Result and conclusion of this paper to reduce losses improving efficiency of solar energy , no pollution (reduce) fast charging as possible as without any disturbance.
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Huang, Yongyi, Atsushi Yona, Hiroshi Takahashi, Ashraf Mohamed Hemeida, Paras Mandal, Alexey Mikhaylov, Tomonobu Senjyu, and Mohammed Elsayed Lotfy. "Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation." Sustainability 13, no. 11 (May 30, 2021): 6163. http://dx.doi.org/10.3390/su13116163.

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Electric vehicle charging station have become an urgent need in many communities around the world, due to the increase of using electric vehicles over conventional vehicles. In addition, establishment of charging stations, and the grid impact of household photovoltaic power generation would reduce the feed-in tariff. These two factors are considered to propose setting up charging stations at convenience stores, which would enable the electric energy to be shared between locations. Charging stations could collect excess photovoltaic energy from homes and market it to electric vehicles. This article examines vehicle travel time, basic household energy demand, and the electricity consumption status of Okinawa city as a whole to model the operation of an electric vehicle charging station for a year. The entire program is optimized using MATLAB mixed integer linear programming (MILP) toolbox. The findings demonstrate that a profit could be achieved under the principle of ensuring the charging station’s stable service. Household photovoltaic power generation and electric vehicles are highly dependent on energy sharing between regions. The convenience store charging station service strategy suggested gives a solution to the future issues.
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Tan, Xian Qiu, Sheng Chun Yang, Yan Ping Fang, and Dong Xue. "Discussion on Operation Modes to the Electric Vehicle Charging Station." Advanced Materials Research 875-877 (February 2014): 1827–30. http://dx.doi.org/10.4028/www.scientific.net/amr.875-877.1827.

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Electric vehicle charging station provides power supply for electric vehicles running, and it is the most important supporting infrastructure of electric vehicles. The article analyses three modes of electric vehicle charging station charging methods, discusses the advantages and disadvantages of each model, gives the developing trend of the pattern of the operation of electric vehicles, and provides some effective suggestions for electric vehicle charging station for the future.
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Zhao, Shu Qiang, and Zhi Wie Li. "The Optimization Model of Planning Electric Vehicle Charging Station." Applied Mechanics and Materials 672-674 (October 2014): 1183–88. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.1183.

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Aiming at the problem of electric vehicle charging station planning, the clients of fast charging stations is analyzed. The optimal mathematical model about siting of electric vehicle charging stations is proposed based on the city's geographic information. We obtain the optimal location of charging stations by charging convenient factor as a constraint. And divide the load area which is served by each charging station by the Voronoi. According to the load which is served by each charging station, this paper designs the optimal battery charger number of each charging station with the Queuing Theory. Finally, optimize the charging convenient factor using the total cost as objective function. The analysis of examples verifies the effectiveness and the practicability of the proposed planning approach.
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Diaz-Londono, Cesar, Luigi Colangelo, Fredy Ruiz, Diego Patino, Carlo Novara, and Gianfranco Chicco. "Optimal Strategy to Exploit the Flexibility of an Electric Vehicle Charging Station." Energies 12, no. 20 (October 10, 2019): 3834. http://dx.doi.org/10.3390/en12203834.

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The increasing use of electric vehicles connected to the power grid gives rise to challenges in the vehicle charging coordination, cost management, and provision of potential services to the grid. Scheduling of the power in an electric vehicle charging station is a quite challenging task, considering time-variant prices, customers with different charging time preferences, and the impact on the grid operations. The latter aspect can be addressed by exploiting the vehicle charging flexibility. In this article, a specific definition of flexibility to be used for an electric vehicle charging station is provided. Two optimal charging strategies are then proposed and evaluated, with the purpose of determining which strategy can offer spinning reserve services to the electrical grid, reducing at the same time the operation costs of the charging station. These strategies are based on a novel formulation of an economic model predictive control algorithm, aimed at minimising the charging station operation cost, and on a novel formulation of the flexibility capacity maximisation, while reducing the operation costs. These formulations incorporate the uncertainty in the arrival time and state of charge of the electric vehicles at their arrival. Both strategies lead to a considerable reduction of the costs with respect to a simple minimum time charging strategy, taken as the benchmark. In particular, the strategy that also accounts for flexibility maximisation emerges as a new tool for maintaining the grid balance giving cost savings to the charging stations.
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B C, Sagar. "Solar Powered Electric Vehicle Charging Station." International Journal for Research in Applied Science and Engineering Technology 9, no. VIII (August 15, 2021): 937–41. http://dx.doi.org/10.22214/ijraset.2021.37016.

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While electric vehicles are generally seen as clean vehicles, they are not completely clean because the production of electricity might generate emissions as well. This paper on a solar powered electric vehicle charging station is a working solution to close the gap in achieving a truly renewable and clean vehicle. The currently scenario of today solar energy ecosystem is that, it is highly unstructured and localized. There are about 50 solar power plants in India but none of them are connect in a manner that there would be a method to perform analytical analysis of the solar energy produced. This paper aims to finding a possible method to connect the solar powered electric vehicle charging station and to perform analytical operations to increase efficiency of Solar Energy.
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Li, Zong Feng, Chun Lin Guo, Jun Chen, Zhe Ci Tang, Wen Chen, Ya Ling Wang, Xiang Zhen Li, and Qing Hai Ou. "A Two-Step Method of Optimal Planning for Electric Vehicle Charging Stations Location." Advanced Materials Research 953-954 (June 2014): 1338–41. http://dx.doi.org/10.4028/www.scientific.net/amr.953-954.1338.

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As a promising transport in the future, electric vehicles plays an important role in people's lives and energy conservation. Planning of electric vehicle charging stations has a far-reaching significance for the popularity of electric vehicles. In this paper, we discuss the siting problem of electric vehicle charging station and propose a two-step method of optimization method. Firstly, we establish a charging station location model, then use Voronoi diagram to determine the preliminary zone, finally we get this problem optimally solved by immune algorithm.The example verifies feasibility of this model.
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Wang, Zhen Po, Peng Liu, Hai Bin Han, Chun Lu, and Tao Xin. "A Distribution Model of Electric Vehicle Charging Station." Applied Mechanics and Materials 44-47 (December 2010): 1543–48. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.1543.

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The location and the overall arrangement of the charging stations is an important problem with the development of electric vehicles. It is related to the charging needs, city planning, service level of charging station, geographic location and competitive ability and so on. A distribution model of EV charging station is introduced in the paper. In order to describe the model preferably, this paper introduces the attractive factor of charging stations and the area-different factor. The model can give the charging station rational positions by analyzing the data of the traffic flow and the electric-consuming-rate of cars on the road. A case study is given to illustrate the applying the model.
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Dissertations / Theses on the topic "Electric vehicle charging station"

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Algvere, Caroline. "Designing Electric Vehicle Charging Station Information." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-415168.

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The electric vehicle industry is under rapid development and the fleet of chargeable cars in society is increasing fast. As a result, a high demand for public chargers has emerged. Simultaneous to the expansion of the electric vehicle fleet and charging infrastructure the power grid is occasionally highly strained. Additionally, factors like cities expanding and the digitization of society also have a large effect on the power grid. This master's thesis investigates the characteristics of electric vehicle users and presents a prototype of an information display for electric vehicle charging stations. The design is is based on the user studies and founded in theory about sustainable user behaviour with the goal of encouraging behaviours that minimize the strain on the local power grid of Uppsala. It concerns the research topic of how to design for sustainable behaviour and address research questions of how to design electric vehicle charging station information to communicate multiple charging alternatives to a broad variety of users. The work reveals that electric vehicle users suffer from the charging infrastructure being underdeveloped, feel frustration towards payment solutions available and lack information regarding electric vehicle use. Also, electric vehicle user's common passion for tech and environmental consciousness are revealed in the study. These facts are used as the foundation for the mobile application design prototype suggested.
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Eltoumi, Fouad. "Charging station for electric vehicle using hybrid sources." Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCA009.

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Une plus grande utilisation des véhicules électriques (VE) et hybrides rechargeables exige une conception efficace des stations de recharge pour fournir des taux de charge appropriés. Le raccordement d'une station sur le réseau électrique conventionnel provoquerait des perturbations, ce qui augmenterait le coût de la recharge. Par conséquent, dans ce scénario, l'utilisation de sources renouvelables sur site telles que l'énergie photovoltaïque (PV) en appui au réseau conventionnel peut augmenter les performances de la station de recharge. Dans cette thèse, une source PV est utilisée conjointement avec le réseau pour compléter la charge des VE. Cependant, le PV est connu pour sa nature intermittente qui dépend fortement des conditions géographiques et météorologiques. Ainsi, pour compenser l'intermittence du PV, un système de stockage à batterie (BSS) est combiné avec le PV dans un système raccordé au réseau, fournissant un fonctionnement stable de la station de recharge PV hybride.En général, les stations de recharge hybrides devraient être rentables, efficientes et fiables pour répondre aux besoins variables de la charge des VE dans différents scénarios. Dans cette thèse, une stratégie efficace de gestion hiérarchique de l'énergie est proposée et appliquée pour maximiser l'énergie photovoltaïque sur site, pour répondre à la charge variable des VE en utilisant une réponse rapide du BSS et en réduisant la sollicitation de réseau. Cette stratégie globale améliore la performance ainsi que la fiabilité et la rentabilité.Un étage de conversion de puissance bidirectionnel efficace est introduit pour le BSS sous la forme d'un convertisseur buck-boost entrelacé pour assurer le fonctionnement du BSS et réduire les pertes pendant la phase de conversion. Cette topologie a des caractéristiques qui permettent d'améliorer les ondulations du courant et par conséquent, d'augmenter considérablement la qualité de l'énergie. De même, pour extraire la puissance maximale du système PV dans des conditions météorologiques intermittentes, une MPPT est utilisée en même temps que le convertisseur élévateur entrelacé pour assurer la continuité de la puissance de la source PV. De même, pour l'étage de charge des véhicules, afin de répondre aux demandes dynamiques de puissance des VE ; tout en maintenant l'équilibre entre les quantités de production disponibles, un convertisseur d'entrelacement est proposé en complément de la stratégie de sous-gestion. En particulier, cette étape de conversion et de gestion porte sur la faible utilisation du réseau notamment lors de pointes de puissance. Ceci diminue considérablement la perturbation sur le réseau, surtout aux heures de pointe, et améliore donc la performance du système dans son ensemble.Pour exploiter l'ensemble du système dans des conditions souhaitables, une stratégie de gestion de l'énergie en ligne est proposée. Cette stratégie en temps réel fonctionne de manière hiérarchique, en s'initialisant à partir d'une utilisation maximale de la source PV, puis en utilisant le BSS pour compléter l'alimentation et en utilisant le réseau en cas de conditions intermittentes ou lorsque la quantité de PV est faible. La stratégie de gestion assure un fonctionnement fiable du système, tout en maximisant l'utilisation du PV, en répondant à la demande des VE et en maximisant la durée de vie du BSS. Dans cette thèse, un système de charge hybride basé sur le PV, le BSS et le réseau conventionnel est proposé pour répondre aux besoins de charge des VE. Une étape efficace de conversion de l'énergie a été proposée en utilisant des convertisseurs entrelacés de type buck-boost pour améliorer la qualité de l'énergie et, en fin de compte, une stratégie de gestion en ligne est développée pour maximiser l'utilisation de l'énergie renouvelable, en insérant moins de stress sur le réseau et en améliorant l'utilisation du BSS
Higher penetration of electric vehicles (EV) and plug-in hybrid electric vehicles requires efficient design of charging stations to supply appropriate charging rates. This would trigger stress on conventional grid, thus increasing the cost of charging. Therefore, in this scenario the use of on-site renewable sources such as photovoltaic (PV) energy alongside to the conventional grid can increase the performance of charging station. In this thesis, a PV source is used in conjunction with grid to supplement EV load. However, the PV is known for its intermittent nature that is highly dependent on geographical and weather conditions. So, to compensate the intermittency of PV, a battery storage system (BSS) is combined with the PV in a grid-tied system, providing a stable operation of hybrid PV based charging station.Generally, hybrid sources based charging station should be cost effective, efficient, and reliable to supplement the variable needs of EVs load in different scenarios. In this thesis, efficient hierarchical energy management strategy is proposed and applied to maximize on-site PV energy, to meet the variable load of EVs using quick response of BSS and putting less stress on grid. This strategy overall improves the performance and is reliable and cost-effective.An efficient bidirectional power conversion stage is introduced for BSS in the form of interleaved buck-boost converter to ensure the safe operation of BSS and reduce the losses during conversion stage. This topology has characteristics to improve the current ripples and therefore, increase the power quality drastically. Similarly, to extract the maximum power from PV system under intermittent weather conditions, MPPT is used alongside with interleaved boost converter to ensure the continuity of power from PV source. Similarly, for vehicles charger stage, to meet the dynamic power demands of EVs; while, keeping the balance between available generation amounts, interleave converter is proposed combined to sub-management strategy. Particularly, this conversion stage and management addresses the low utilization of grid sources for charging purpose when, peak load is present at grid side. This charging behaviour greatly decreases the stress on grid especially at peak hours and therefore, improves the performance of system in overall.To operate whole system under desirable conditions, an online energy management strategy is proposed. This real-time strategy works in hierarchical manner, initializing from maximized utilization of PV source, then using BSS to supplement power and utilizing grid during intermittent conditions or when there is low amount of PV. The management strategy ensure reliable operation of system, while maximizing the PV utilization, meeting the EVs demand and maximizing the life the BSS.In this thesis, a hybrid charging system based on PV, BSS and conventional grid is proposed to support the needs of EVs load. Efficient energy conversion stage has been proposed using interleave buck-boost converters to improve the quality of power and at the end, an online management strategy is developed to maximize the renewable energy utilization, inserting lesser stress on grid and improving the utilization of BSS to improve its life
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Du, Yunke. "PEV Charging Demand Estimation and Selection of Level 3 Charging Station." University of Akron / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=akron1367243693.

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Atterby, Alfred, Jakub Bluj, and Elias Sjögren. "Potential for electric vehicle smart charging station expansion at Fyrisskolan." Thesis, Uppsala universitet, Institutionen för teknikvetenskaper, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-352636.

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The purpose of this bachelor thesis is to investigate the potential for electric vehicle charging at the high school Fyrisskolan, located in central Uppsala. The idea relies on charging electric vehicles (EV:s) outside of the hours of peak power consumption of the school which in this report is assumed to be solved by a suitable smart charger. In this project, various stochastic models are built to simulate solar energy production and school energy consumption using data collected from various sources. This generated data along with  driving distances and EV:s energy consumptions are used to calculate the available energy for EV charging. The available energy is then used to distinguish a minimal, mean and maximal amount of cars that could potentially be charged outside Fyrisskolan for each chosen month. The data collected is taken from December, March and June. Calculations and simulations are done in MATLAB. Results show that with available energy outside the peak energy consumption hours, there is a possibility to charge around 104 EV:s in one work day. The main conclusion is that there is not only a big potential to expand the charging of EV:s outside the school by installing smart charging stations in a technical view, but also a desire from employees at the school and neighbours living near it, to charge their future electric vehicles.
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Wu, Fei. "Electric Vehicle Charging Network Design and Control Strategies." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1479900508609434.

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Österberg, Viktor. "Electric Vehicle Charging Station Markets : An analysis of the competitive situation." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2018.

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Electric Vehicles represent a small niche market today, but is predicted to grow rapidly over the next years. In order to prepare for this upcoming trend it is the networks of Electric Vehicle Charging Stations (EVCS) must expand, leading to an increasing demand for EVCSs. The EVCS market is thus becoming increasingly more popular to companies, and therefore this study’s purpose is to investigate this market and its competitive situation. The method used in this study includes a brief market analysis and a competitor analysis. The market analysis includes identification of the EVCS markets together assessing the future of the markets, and identification of EVCS market drivers and restraints. The competitor analysis includes competitor identification, classification and analysis. The top ten competitors are analyzed by the use of document content analysis, the analysis involves understanding the competitors’ target customers, how they do business and how their marketing material is structured. The three most promising EVCS markets, both currently and in the future, are the Asia Pacific, Europe and the North America markets. Most of the top competitors are active within these three markets. Regional developments, and market drivers and restraints of these markets have been identified. The opportunities in the EVCS markets are many as they are relatively unexploited markets without any actual market leaders, and also that all markets are predicted to grow at a very high rate over the coming decade in parallel with the projected mass adoption if Electric Vehicles (EVs).
Idag utgör elfordon endast en liten nischmarknad i transportmarknaden, men denna förväntas växa snabbt under de närmaste åren. För att kunna hantera marknadsetableringen av elfordon måste elfordonsladdningsinfrastrukturen byggas ut, vilket leder till en ökad efterfrågan på elfordonsladdningsstationer. Elfordonsladdningsmarknaden förespås således bli allt mer intressant för företag. Detta examensarbete genomförs på grund av detta växande intresse, då studiens syfte är att undersöka elfordonsladdstationsmarknaden och dess konkurrenssituation. Metoden som används i denna studie inbegriper en kort marknadsanalys och en konkurrensanalys. Marknadsanalysen innehåller identifiering av elfordonsladdningsmarknaderna, vad som driver och hindrar marknaderna, och en bedömning av hur framtiden ser ut för marknaderna. I konkurrensanalysen ingår identifiering, klassificering och analys av de olika konkurrenterna. De tio mest konkurrenskraftiga konkurrenterna analyseras med hjälp av dokumentinnehållsanalys, syftet med analysen är att förstå konkurrenternas målgrupper, hur de gör affärer och hur deras marknadsföringsmaterial är strukturerad. De tre mest lovande elfordonsladdningsmarknaderna, både nu och i framtiden, är marknaderna i Asien och Stillahavsområdet, Europa och Nordamerika. De flesta av de analyserade konkurrenterna är verksamma inom dessa tre marknader. Den regionala utvecklingen, och vad som driver och begränsar marknaderna har identifierats för de tre mest lovande marknaderna. Eftersom dessa marknader är relativt oexploaterade i samband med att de förväntas växa med väldigt hög takt det kommande decenniet parallellt med massanvändningen av elfordon är möjligheterna många för de företag som inriktar sig mot elbilsladdning.
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Greene, Briun. "How to Develop the Electric Vehicle Charging Station Infrastructure in China." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1437409084.

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Högberg, Tomas. "Self Service Customer Support of Electric Vehicle Charging Stations." Thesis, KTH, Kraft- och värmeteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-277818.

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The aim of this master thesis is to develop a suggested methodology for how to use Mavenoid infrastructure to improve customer support of DEFA EV chargers. Mavenoid is a company that helps other companies automate customer support, especially troubleshooting. This is done with Mavenoid models, interactive selfhelp tools that guide end users without technical knowledge through the troubleshooting process. Mavenoid models provide value both by deflecting cases (the end user solves the problem on their own using the model) and triaging cases (collect relevant information about the problem before escalating the case to a human support agent) The main methodology to develop a suggested methodology was learning by doing, using the suggested methodology to actually implement Mavenoid models available to end users on DEFA’s home page. This was complemented with a literature review, interviews and data analysis from model usage. The suggested methodology is to iteratively follow the steps of deciding which models to build, make priorities within these models, build the models, analyze their performance and continuously improve the models. To decide models, carefully evaluate DEFA’s support situation to decide where Mavenoid models would have the greatest impact. Force yourself to make quantitative assumptions to estimate a payback time for each possible model. For each model, carefully prioritize what to include and where the focus should be using estimates of frequency, value and time to model. Build the models to maximize deflection and triage and minimize abandoned sessions. Collect and analyze data from model usage and use this information to improve the models. To prioritize between possible improvements, force yourself to make quantitative assumptions of value and time to model and rank improvements by payback time. Limit the improvements you make either by time available or desired payback time. The potential business opportunity between Mavenoid and its customers is more attractive the more support cases the customer has and the larger fraction of end users that use Mavenoid. The business opportunity varies greatly with assumptions that are very difficult to estimate accurately at the early stages of a Mavenoid implementation. This indicates that Mavenoid models should be implemented step by step and assumptions updated when more data is available. Implementing Mavenoid models can be both positive and negative from a sustainable development perspective. They could encourage people to repair products instead of replacing them, scale renewable energy technology faster and remove boring and repetitive tasks from support staff. On the other hand, they might not be appreciated by all end users, could lead to increased electricity consumption and potential unemployment for support staff. Being about a largely unresearched topic, the results in this thesis are relatively subjective. This suggested methodology was used and proved to work to implement Mavenoid models for DEFA EV charging stations but it should be seen as one possible methodology, not the confirmed best methodology.
Syftet med detta examensarbete är att utveckla en metodologi för hur Mavenoids teknologi kan användas till att förbättra kundsupporten för DEFAs elbilsladdare. Mavenoid är ett företag som hjälper andra företag att automatisera kundsupport, särskilt felsökning. Detta görs med Mavenoidmodeller, interaktiva självhjälpsverktyg som guidar slutanvändare utan teknisk kunskap genom felsökningsprocessen. Mavenoidmodeller ger värde både genom att slutanvändaren löser problemet på egen hand genom att använda modellen (deflection) och genom att samla relevant information om problemet innan ärendet eskaleras till teknisk support (triage). Den huvudsakliga metoden för att utveckla metodologin var att lära genom att göra, faktiskt implementera Mavenoidmodeller och göra de tillgängliga för slutanvändare på DEFA: s hemsida. Detta kompletterades med en litteraturöversikt, intervjuer och dataanalys av hur modellerna användes. Den föreslagna metodologin är att iterativt följa stegen besluta vilka modeller som ska byggas, prioritera inom dessa modeller, bygga modellerna, analysera data från dem och kontinuerligt förbättra modellerna. För att bestämma modeller, utvärdera DEFAs supportsituation noggrant för att bestämma var Mavenoid-modellerna skulle ha störst inverkan. Tvinga dig själv att göra kvantitativa antaganden för att uppskatta en återbetalningstid för varje möjlig modell. För varje modell ska du noggrant prioritera vad du ska inkludera och var fokus ska vara genom att använda uppskattningar av frekvens, värde och tid att modellera. Bygg modellerna för att maximera deflection och triage och minimera övergivna sessioner. Samla och analysera data från modellerna och använd denna information för att förbättra modellerna. För att prioritera mellan möjliga förbättringar, tvinga dig själv att göra kvantitativa antaganden om värde och tid att modellera och rangordna förbättringar efter återbetalningstid. Begränsa de förbättringar du gör antingen utifrån tillgänglig tid eller önskad återbetalningstid. Den potentiella affärsmöjligheten mellan Mavenoid och dess kunder är mer attraktiv ju fler supportärenden kunden har och ju större andel slutanvändare som använder Mavenoid. Affärsmöjligheten varierar kraftigt med antaganden som är mycket svåra att uppskatta i början av ett projekt att implementera Mavenoidmodeller. Detta indikerar att Mavenoidmodeller bör implementeras steg för steg och antaganden uppdateras när mer data finns tillgängligt. Implementering av Mavenoid-modeller kan vara både positivt och negativt sett till hållbar utveckling. De kan uppmuntra människor att reparera produkter istället för att byta ut dem, skala upp förnybar energiteknologi snabbare och ta bort tråkiga och repetitiva uppgifter från teknisk support. Å andra sidan kanske de inte uppskattas av alla slutanvändare, kan leda till ökad elförbrukning och potentiell arbetslöshet för de som jobbar inom teknisk support. Eftersom examensarbetet handlar om ett relativt outforskat ämne är resultaten relativt subjektiva. Denna föreslagna metodologi användes och visade sig fungera för att implementera Mavenoidmodeller för DEFAs elbilsladdare men den bör ses som en möjlig metodologi, inte den bekräftat bästa metodologin.
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de, Freige Makram. "Design and simulation of a fast-charging station for plug-in hybrid electric vehicle (PHEV) batteries." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103758.

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With the increasing interest in green technologies in transportation, plug-in hybrid electric vehicles (PHEV) have proven to be the best short-term solution to minimize greenhouse gas emissions. Despite such interest, conventional vehicle drivers are still reluctant in using such a new technology, mainly because of the long duration (4-8 hours) required to charge PHEV batteries with the currently existing Level I and II chargers. For this reason, Level III fast-charging stations capable of reducing the charging duration to 10-15 minutes are being considered. The present thesis focuses on the design of a fast-charging station that uses, in addition to the electrical grid, two stationary energy storage devices: a flywheel energy storage and a supercapacitor. The power electronic converters used for the interface of the energy sources with the charging station are designed. The design also focuses on the energy management that will minimize the PHEV battery charging duration as well as the duration required to recharge the energy storage devices. For this reason, an algorithm that minimizes durations along with its mathematical formulation is proposed, and its application in fast charging environment will be illustrated by means of two scenarios.
Depuis le développement de l'intérêt porté aux technologies propres appliquées au domaine de l'automobile et du transport, les véhicules hybrides et électriques rechargeables (VHER) sont reconnus comme le meilleur compromis qui diminuerait les émissions de gaz a effet de serre. Malgré ce progrès pour l'environnement, la plupart des usagers de véhicules conventionnels refusent de s'adapter à cette nouvelle technologie a cause du long temps requis (4 à 8 heures) pour recharger les batteries des VHERs si les chargeurs de Niveau I et II existants sont utilisés. Pour cette raison, les stations de recharge rapide de Niveau III sont largement considérées. La présente thèse propose une station qui emploi comme sources d'énergie le réseau électrique ainsi que deux sources de stockage d'énergie : une roue d'inertie et un supercondensateur. Les convertisseurs qui permettent l'interface de ces sources avec le chargeur sont également conçus et dimensionnés en énergie. Afin d'optimiser le temps requis pour recharger la batterie du VHER ainsi que le temps requis pour recharger les sources de stockage, un algorithme est proposé avec son application à la technologie de recharge rapide. Deux différents scenarios sont mis en oeuvre pour illustrer l'efficacité de cet algorithme.
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Gogoana, Radu. "Assessing the viability of level III electric vehicle rapid-charging stations." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/59912.

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Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 33).
This is an analysis of the feasibility of electric vehicle rapid-charging stations at power levels above 300 kW. Electric vehicle rapid-charging (reaching above 80% state-of-charge in less than 15 minutes) has been demonstrated, but concerns have been raised about the high levels of electrical power required to recharge a high-capacity battery in a short period of time. This economic analysis is based on an existing project run by MIT's Electric Vehicle Team, of building a 200-mile range battery electric sedan capable of recharging in 10 minutes. The recharging process for this vehicle requires a power source capable of delivering 350 kW; while this is possible in controlled laboratory environments, this thesis explores the viability of rapid-charging stations on the grid-scale and their capability of servicing the same volume of vehicles as seen by today's gas stations. At this volume, building a rapid-charging station is not only viable, but has the potential to become a lucrative business opportunity.
by Radu Gogoana.
S.B.
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Books on the topic "Electric vehicle charging station"

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K, Kokula Krishna Hari, ed. A Multi-Function Conversion Technique for Electric Vehicle Charging Station. Chennai, India: Association of Scientists, Developers and Faculties, 2016.

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Richard, Alice. Electric Vehicle Charging Stations at Airport Parking Facilities. Washington, D.C.: Transportation Research Board, 2014. http://dx.doi.org/10.17226/22390.

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Kurani, Kenneth S. Consumer response to plug-in hybrid electric vehicles: Vehicle design priorities, driving and charging behavior, and energy impacts. Davis, California]: [California Energy Commission], 2012.

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Committee, New Jersey Legislature General Assembly Environment and Solid Waste. Committee meeting of Assembly Environment and Solid Waste Committee: Assembly bill nos. 409 and 2439 : discussion on the implementation of the phase II California Low Emission Vehicle program beginning in calendar year 2006. Trenton, N.J: Office of Legislative Services, Public Information Office, Hearing Unit, 2002.

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Zverovich, Vadim. Modern Applications of Graph Theory. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198856740.001.0001.

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This book discusses many modern, cutting-edge applications of graph theory, such as traffic networks and Braess’ paradox, navigable networks and optimal routing for emergency response, backbone/dominating sets in wireless sensor networks, placement of electric vehicle charging stations, pedestrian safety and graph-theoretic methods in molecular epidemiology. Because of the rapid growth of research in this field, the focus of the book is on the up-to-date development of the aforementioned applications. The book will be ideal for researchers, engineers, transport planners and emergency response specialists who are interested in the recent development of graph theory applications. Moreover, this book can be used as teaching material for postgraduate students because, in addition to up-to-date descriptions of the applications, it includes exercises and their solutions. Some of the exercises mimic practical, real-life situations. Advanced students in graph theory, computer science or molecular epidemiology may use the problems and research methods presented in this book to develop their final-year projects, master’s theses or doctoral dissertations; however, to use the information effectively, special knowledge of graph theory would be required.
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IET code of practice on electric vehicle charging equipment installation. The Institution of Engineering and Technology, 2012.

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S, Yau Timothy, Zaininger H. W, Bernard M. J, Heitner Kenneth, Singh M. K, Saricks C. L, Electric Power Research Institute, United States. Dept. of Energy, and United States. Dept. of Energy. Electric and Hybrid Propulsion Division, eds. Utility emissions associated with electric and hybrid vehicle (EHV) charging: Interim report. Washington, DC: U.S. Dept. of Energy, Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Transportation Technologies, Electric and Hybrid Propulsion Division, 1993.

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Ma, Zhongjing, and Suli Zou. Efficient Auction Games: Theories, Algorithms and Applications in Smart Grids & Electric Vehicle Charging. Springer, 2020.

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Book chapters on the topic "Electric vehicle charging station"

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Xu, Longlong, Wutao Lin, Xiaorong Wang, Zhenhui Xu, Wei Chen, and Tengjiao Wang. "ChargeMap: An Electric Vehicle Charging Station Planning System." In Web and Big Data, 337–40. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63564-4_31.

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Ahmad, Aqueel, Yasser Rafat, Samir M. Shariff, and Rakan Chabaan. "Smart Microgrid-Integrated EV Wireless Charging Station." In Electric Vehicle Integration in a Smart Microgrid Environment, 267–78. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9780367423926-11.

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Thukral, Manish Kumar. "Blockchain-Based Smart Contract Design for Crowdfunding of Electrical Vehicle Charging Station Setup." In Electric Vehicles, 187–98. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-9251-5_11.

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Li, Kai, and Shuai Wang. "Electric Vehicle Charging Station Deployment for Minimizing Construction Cost." In Big Data Analytics and Knowledge Discovery, 471–85. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64283-3_35.

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Zhang, Yu, Xiangtao Liu, Tianle Zhang, and Zhaoquan Gu. "Review of the Electric Vehicle Charging Station Location Problem." In Communications in Computer and Information Science, 435–45. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1304-6_35.

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Ouertani, Mohamed Wajdi, Ghaith Manita, and Ouajdi Korbaa. "Improved Genetic Algorithm for Electric Vehicle Charging Station Placement." In Intelligent Decision Technologies, 37–57. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2765-1_4.

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Gupta, Rudraksh S., Arjun Tyagi, V. V. Tyagi, Y. Anand, A. Sawhney, and S. Anand. "Renewable Energy-Driven Charging Station for Electric Vehicles." In Energy Systems and Nanotechnology, 57–78. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1256-5_5.

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Laverty, David, Kang Li, and Jing Deng. "Data Communications for Intelligent Electric Vehicle Charging Stations." In Communications in Computer and Information Science, 543–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45261-5_57.

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Jordán, Jaume, Pasqual Martí, Javier Palanca, Vicente Julian, and Vicente Botti. "Interurban Electric Vehicle Charging Stations Through Genetic Algorithms." In Lecture Notes in Computer Science, 101–12. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86271-8_9.

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Li, Min, Wuhong Wang, Hongfei Mu, Xiaobei Jiang, Prakash Ranjitkar, and Tao Chen. "Demand Forecasting-Based Layout Planning of Electric Vehicle Charging Station Locations." In Green Intelligent Transportation Systems, 1009–21. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3551-7_81.

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Conference papers on the topic "Electric vehicle charging station"

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Lam, Albert Y. S., Yiu-Wing Leung, and Xiaowen Chu. "Electric vehicle charging station placement." In 2013 IEEE International Conference on Smart Grid Communications (SmartGridComm). IEEE, 2013. http://dx.doi.org/10.1109/smartgridcomm.2013.6688009.

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Tonape, Abhishek, and Suryakant H.Pawar. "Pulse Current Charging Station for Electric Vehicle Charging." In 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE). IEEE, 2020. http://dx.doi.org/10.1109/ic-etite47903.2020.358.

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Tanveer, Md Sohail, Sunil Gupta, Rahul Rai, Neeraj Kumar Jha, and Mohit Bansal. "Solar based electric vehicle charging station." In 2019 2nd International Conference on Power Energy, Environment and Intelligent Control (PEEIC). IEEE, 2019. http://dx.doi.org/10.1109/peeic47157.2019.8976673.

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Ganiger, Manjush, Maneesh Pandey, Rahul Wagh, and Rakesh Govindasamy. "Gas Turbine Based Electric Vehicle Charging Station." In ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/gt2021-60176.

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Abstract Transition towards electric vehicles (EV) is the key enabler for fighting against climate change as well as for sustainable future. However, to build more confidence on EV transition, availability of charging infrastructure is key. One of the important criterions for vehicle charging station is to have a stable electricity source that can meet varying charging demand. The paper attempts to explore the eco-system of self-sustainable and quasi-renewable charging infrastructure. This paper outlines a circular economy model for EV charging station (EVCS) using a gas turbine from the Baker Hughes™ portfolio. The proposed solution includes Solid Oxide Electrolyzer and a carbon capture unit, integrated to the gas turbine. This integrated system is decarbonized using the hydrogen generated by the electrolysis unit. Proposed solution on EVCS can charge about 1500 EVs in half a day of operation (50% power split). Solution is lucrative and has attractive return on investment. The solution here is having high power density, compared to the actual renewable energy dependent charging stations. The solution is flexible to incorporate Power-to-X conversions. Modular nature of the solution makes it easy to implement in city limits as well as in remote locations, along the highways, where grid availability can be challenging.
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Arancibia, Arnaldo, and Kai Strunz. "Modeling of an electric vehicle charging station for fast DC charging." In 2012 IEEE International Electric Vehicle Conference (IEVC). IEEE, 2012. http://dx.doi.org/10.1109/ievc.2012.6183232.

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Lobato, Salatiel de C., Jonathan H. D. G. Pinto, Renan N. de M. Carneiro, Guilherme F. Avelar, Jose A. Valentim, and Andre A. Ferreira. "Development of an electric vehicle charging station." In 2018 Simposio Brasileiro de Sistemas Eletricos (SBSE) [VII Brazilian Electrical Systems Symposium (SBSE)]. IEEE, 2018. http://dx.doi.org/10.1109/sbse.2018.8395582.

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Li, Jinlong, Yi Tang, and Li Zhou. "Electric Vehicle Charging Station Location Problem Research." In Fifth International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784479384.336.

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Dong, Yingshuai. "Electric vehicle charging station quantity forecasting model." In MATERIALS SCIENCE, ENERGY TECHNOLOGY AND POWER ENGINEERING II (MEP2018). Author(s), 2018. http://dx.doi.org/10.1063/1.5041162.

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Saadat, Shahriar, Samantha Maingot, and Sahba Bahizad. "Electric Vehicle Charging Station Security Enhancement Measures." In 2020 5th IEEE Workshop on the Electronic Grid (eGRID). IEEE, 2020. http://dx.doi.org/10.1109/egrid48559.2020.9330666.

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Pandey, Vartika, and Prem Prakash. "Dynamic management of electric vehicle charging station." In 2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies. IEEE, 2021. http://dx.doi.org/10.1109/icepe50861.2021.9404527.

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Reports on the topic "Electric vehicle charging station"

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Lapsa, Melissa Voss, Norman Durfee, L. Curt Maxey, and Randall M. Overbey. Solar-Assisted Electric Vehicle Charging Station Interim Report. Office of Scientific and Technical Information (OSTI), September 2011. http://dx.doi.org/10.2172/1025858.

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Smith, Margaret. Level 1 Electric Vehicle Charging Stations at the Workplace. Office of Scientific and Technical Information (OSTI), July 2016. http://dx.doi.org/10.2172/1416120.

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Brown, Abby, Stephen Lommele, Alexis Schayowitz, and Emily Klotz. Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: Second Quarter 2020. Office of Scientific and Technical Information (OSTI), January 2021. http://dx.doi.org/10.2172/1763972.

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Brown, Abby, Stephen Lommele, Alexis Schayowitz, and Emily Klotz. Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: First Quarter 2020. Office of Scientific and Technical Information (OSTI), August 2020. http://dx.doi.org/10.2172/1660251.

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Brown, Abby, Stephen Lommele, Alexis Schayowitz, and Emily Klotz. Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: Third Quarter 2020. Office of Scientific and Technical Information (OSTI), May 2021. http://dx.doi.org/10.2172/1783774.

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Brown, Abby, Stephen Lommele, Alexis Schayowitz, and Emily Klotz. Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: Fourth Quarter 2020. Office of Scientific and Technical Information (OSTI), June 2021. http://dx.doi.org/10.2172/1798711.

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Brown, Abby, Alexis Schayowitz, and Emily Klotz. Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: First Quarter 2021. Office of Scientific and Technical Information (OSTI), September 2021. http://dx.doi.org/10.2172/1820581.

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Schey, Steve, and Jim Francfort. Assessment of Charging Infrastructure for Plug-in Electric Vehicles at Naval Air Station Whidbey Island: Task 3. Office of Scientific and Technical Information (OSTI), July 2015. http://dx.doi.org/10.2172/1235203.

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Durfee, Norman, Rick Goeltz, Tim J. LaClair, Melissa Voss Lapsa, L. Curt Maxey, and Randall M. Overbey. Deployment of Solar Assisted and Non-Solar Electric Vehicle Charging Stations in the State of Tennessee, Final Report. Office of Scientific and Technical Information (OSTI), September 2014. http://dx.doi.org/10.2172/1159487.

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Bent, Russell W., Stefan Solntsev, and Feng Pan. Building charging stations for electric vehicles When and where? Office of Scientific and Technical Information (OSTI), September 2011. http://dx.doi.org/10.2172/1092467.

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