Optimal design of the wireless charging electric vehicle

Jang, Young Jae; Ko, Young Dae; Jeong, Sangbae

doi:10.1109/ievc.2012.6183294

Cited by 61 publications

(33 citation statements)

References 2 publications

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“…We also plan to incorporate the remote (wireless) charging and discharging [25] mechanism, so that cost to travel the charging/discharging station can be minimized.…”

Section: Discussionmentioning

confidence: 99%

D2P: Distributed Dynamic Pricing Policyin Smart Grid for PHEVs Management

Misra

Bera

Ojha

2015

IEEE Trans. Parallel Distrib. Syst.

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Future large-scale deployment of plug-in hybrid electric vehicles (PHEVs) will render massive energy demand on the electric grid during peak-hours. We propose an intelligent distributed dynamic pricing (D2P) mechanism for the charging of PHEVs in a smart grid architecture -an effort towards optimizing the energy consumption profile of PHEVs users. Each micro-grid decides real-time dynamic price as home-price and roaming-price, depending on the supply-demand curve, to optimize its revenue. Consequently, two types of energy services are considered -home micro-grid energy, and foreign microgrid energy. After designing the PHEVs' mobility and battery models, the pricing policies for the home-price and the roamingprice are presented. A decision making process to implement a cost-effective charging and discharging method for PHEVs is also demonstrated based on the real-time price decided by the micro-grids. We evaluate and compare the results of distributed pricing policy with other existing centralized/distributed ones. Simulation results show that using the proposed architecture, the utility corresponding to the PHEVs increases by approximately 34% over that of the existing ones for optimal charging of PHEVs.Index Terms-PHEVs, Roaming-price, Micro-grid, Vehicle to Grid (V2G), Grid to Vehicle (G2V), Smart Grid, Dynamic pricing.1045-9219 (c)

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“…We also plan to incorporate the remote (wireless) charging and discharging [25] mechanism, so that cost to travel the charging/discharging station can be minimized.…”

Section: Discussionmentioning

confidence: 99%

D2P: Distributed Dynamic Pricing Policyin Smart Grid for PHEVs Management

Misra

Bera

Ojha

2015

IEEE Trans. Parallel Distrib. Syst.

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“…Mathematical frameworks describing the optimal power transmitter placement and battery capacity for wirelessly charged EVs operating on fixed routes are presented by Ko et al (2012) and Jang et al (2012). He et al (2013a) presented an approach to determine the optimal prices of electricity and roads for wireless power transfer by maximizing social welfare and by considering scenarios of full and partial electrification of roads.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal location of wireless charging facilities for electric vehicles: Flow-capturing location model with stochastic user equilibrium

Riemann¹,

Wang

Busch

2015

Transportation Research Part C: Emerging Technologies

222

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“…Charging stations are capable of p c3 regardless of whether they are simply charging or implementing more advanced "vehicle to grid" technology [7][8][9]. The electrified roads associated with online EVs [102][103][104][105][106] are capable of p c4 .…”

Section: Establish Ten Structurementioning

confidence: 99%

A Hybrid Dynamic System Assessment Methodology for Multi-Modal Transportation-Electrification

Wardt

Farid

2017

Energies

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Abstract:In recent years, electrified transportation, be it in the form of buses, trains, or cars have become an emerging form of mobility. Electric vehicles (EVs), especially, are set to expand the amount of electric miles driven and energy consumed. Nevertheless, the question remains as to whether EVs will be technically feasible within infrastructure systems. Fundamentally, EVs interact with three interconnected systems: the (physical) transportation system, the electric power grid, and their supporting information systems. Coupling of the two physical systems essentially forms a nexus, the transportation-electricity nexus (TEN). This paper presents a hybrid dynamic system assessment methodology for multi-modal transportation-electrification. At its core, it utilizes a mathematical model which consists of a marked Petri-net model superimposed on the continuous time microscopic traffic dynamics and the electrical state evolution. The methodology consists of four steps: (1) establish the TEN structure; (2) establish the TEN behavior; (3) establish the TEN Intelligent Transportation-Energy System (ITES) decision-making; and (4) assess the TEN performance. In the presentation of the methodology, the Symmetrica test case is used throughout as an illustrative example. Consequently, values for several measures of performance are provided. This methodology is presented generically and may be used to assess the effects of transportation-electrification in any city or area; opening up possibilities for many future studies.

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Optimal design of the wireless charging electric vehicle

Cited by 61 publications

References 2 publications

D2P: Distributed Dynamic Pricing Policyin Smart Grid for PHEVs Management

D2P: Distributed Dynamic Pricing Policyin Smart Grid for PHEVs Management

Optimal location of wireless charging facilities for electric vehicles: Flow-capturing location model with stochastic user equilibrium

A Hybrid Dynamic System Assessment Methodology for Multi-Modal Transportation-Electrification

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