Electric vehicle fast charging infrastructure planning in urban networks considering daily travel and charging behavior

Kavianipour, Mohammadreza; Fakhrmoosavi, Fatemeh; Singh, Harprinderjot; Ghamami, Mehrnaz; Zockaie, Ali; Ouyang, Yanfeng; Jackson, Robert

doi:10.1016/j.trd.2021.102769

Cited by 85 publications

(80 citation statements)

References 46 publications

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“…Three-phase bidirectional multilevel AC-DC PFC converters are preferred for new technology high voltage and high power applications. The following factors are considered in the selection of these converters, which are also considered for fast charging (Kavianipour et al, 2021).…”

Section: Selection Criteria Of Three-phase Ac-dc Pfc Converters For Ev Fast Chargingmentioning

confidence: 99%

A Review of Three Phase AC-DC Power Factor Correction Converters for Electric Vehicle Fast Charging

MOLLAHASANOĞLU¹,

Okumuş²

2022

European Journal of Science and Technology

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Electric vehicle charging station for fast DC charging performs AC-DC conversion at off-board. In recent years, three-phase AC-DC power factor correction (PFC) converters are dealt with fast charger. These converters are developed using unidirectional and bidirectional power flow structure. In this study, three-phase AC-DC PFC converter topologies, providing bidirectional power flow, are evaluated in terms of performance. The aim is to present the latest technology of bidirectional multilevel AC-DC PFC converters for EV fast charging. This paper provides a comprehensive and practical review for researchers interested in fast charging infrastructure for electric vehicles.

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Section: Selection Criteria Of Three-phase Ac-dc Pfc Converters For Ev Fast Chargingmentioning

confidence: 99%

A Review of Three Phase AC-DC Power Factor Correction Converters for Electric Vehicle Fast Charging

MOLLAHASANOĞLU¹,

Okumuş²

2022

European Journal of Science and Technology

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“…( ) design for charging station placement optimization that considers trip trajectories and wider array of parameters could be utilized in order to obtain a more operational investment cost and system requirements (Fakhrmoosavi et al, 2021;Ghamami et al, 2020;Kavianipour et al, 2021).…”

Section: Initial System Deploymentmentioning

confidence: 99%

Smart City: A Mobility Technology Adoption Framework Incorporating Surface-Level Technical Analysis

Jazlan¹,

Saedi²,

Zockaie³

et al. 2022

CUS

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Rising urban population, aging infrastructure, and increasing capital maintenance costs call for more efficient use of limited available resources. To address these concerns, the use of technology for urban infrastructure management and operational efficiency comes naturally with emerging technological advancements. Although there have been analyses on how to conceptually design a smart city from the ground up, they are often less applicable in transforming existing cities into smart ones. Retrofitting existing infrastructures requires integration and synergies with existing systems. Given the broad scope of smart cities, this paper equips planners with surface-level considerations in adopting smart mobility solutions. This provides an avenue to assess project feasibility, risk management, and investment requirement. The process is presented via a replicable framework with a use case with simplistic approaches that do not require complex constraints or modeling. The framework streamlines how to deduce a feasible set of user-centric smart solutions, which are then ranked according to their impacts for implementation priority. Middle East Technical University campus located in Ankara (Turkey) is considered for the use case. The main outcomes for the use case are deducing high-impact smart solutions based on the proposed framework. Preliminary system design analyses are showcased for three high-ranked solutions: electric vehicle charging station installation and investment optimization, autonomous electric shuttle system design, and bus network electrification strategies.

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“…A study looked at spot traffic counts in Western Australia coupled with an assumed EV penetration rate of 1% to select sites for future DC Fast charging stations using the criterion of reliability, accessibility and availability of amenities and services [17]. Various simulation-based approaches have been employed in the past for EV fast charging infrastructure planning using simulated trajectories and charging behavior assumptions [18], urban mobility simulations that minimize EV energy consumption [19], as well as mathematical programming models factoring in user convenience and grid connections for low penetration levels of 5% [20]. Data obtained from fast charging stations in Ireland observed 0.18 charges per day per EV user at home and 0.06 charges per day per EV user in public charging locations, thus reinforcing the need for more strategically placed fast charging stations to incentivize more usage in non-peak grid demand times [21].…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Electric and Hybrid Vehicle Usage in Proximity to Charging Infrastructure in Indiana

Desai¹,

Mathew²,

Li³

et al. 2021

JTTs

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This paper explores the movement of connected vehicles in Indiana for vehicles classified by the NHTSA Product Information Catalog Vehicle listing as being either electric (EV) or hybrid electric (HV). Analysis of trajectories from July 12-18, 2021 for the state of Indiana observed nearly 33,300 trips and 267,000 vehicle miles travelled (VMT) for the combination of EV and HV. Approximately 53% of the VMT occurred in just 10 counties. For just EVs, there were 9814 unique trips and 64,700 Electric Vehicle Miles Traveled (EVMTs) in total. A further categorization of this revealed that 18% of these EVMTs were on Interstate roadways and 82% on non-interstate roads. Proximity analysis of existing DC Fast charging stations in relation to interstate roadways revealed multiple charging deserts that would be most benefited by additional charging capacity. Eleven roadway sections among the 9 interstates were found to have a gap in available DC fast chargers of 50 miles or more. Although the connected vehicle data set analyzed did not include all EV's the methodology presented in this paper provides a technique that can be scaled as additional EV connected vehicle data becomes available to agencies. Furthermore, it emphasizes the need for transportation agencies and automotive vendors to strengthen their data sharing partnerships to help accelerate the adoption of EV and reduce consumer range anxiety with EV. Graphics are included that illustrate examples of counties that are both overserved and underserved by charging infrastructure.

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Electric vehicle fast charging infrastructure planning in urban networks considering daily travel and charging behavior

Cited by 85 publications

References 46 publications

A Review of Three Phase AC-DC Power Factor Correction Converters for Electric Vehicle Fast Charging

A Review of Three Phase AC-DC Power Factor Correction Converters for Electric Vehicle Fast Charging

Smart City: A Mobility Technology Adoption Framework Incorporating Surface-Level Technical Analysis

Analysis of Electric and Hybrid Vehicle Usage in Proximity to Charging Infrastructure in Indiana

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