Rapid-Charging Navigation of Electric Vehicles Based on Real-Time Power Systems and Traffic Data

Guo, Qinglai; Xin, Shujun; Sun, Hongbin; Li, Zhengshuo; Zhang, Boming

doi:10.1109/tsg.2014.2309961

Cited by 155 publications

(66 citation statements)

References 40 publications

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“…This can not be overlooked as it is the most important feature of a vehicle in future smart city, especially for fast charging. The works in [3], [5], [6] implement charging plans for all EVs based on the minimized queuing time. Results in [4] show that considering number of other EVs parking at the CS outperforms that considering the distance to the CS, achieves a shorter charging waiting time particularly given a high EV density.…”

Section: A Research On Ev Charging Managementmentioning

confidence: 99%

“…This means the EV with an earlier arrival will be scheduled with a higher priority. Note that the FCFS policy has been widely applied by previous works [5]- [7] on CS-selection problem.…”

Section: B System Cycle Of Ev Charging Managementmentioning

confidence: 99%

“…In literature, the scheme selecting the CS with the closest distance [4] and that with the minimum queuing time [5]- [7] have been studied. However, a potential charging hotspot may happen if many EVs travel towards the same CS for charging, due to that the decision just considers the local condition of CSs (e.g., availability of charging slots).…”

Section: Introductionmentioning

confidence: 99%

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Applying DTN routing for reservation-driven EV Charging management in smart cities

Cao

Zhang

Wang

et al. 2017

2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC)

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Abstract-Charging management for Electric Vehicles (EVs)on-the-move (moving on the road with certain trip destinations) is becoming important, concerning the increasing popularity of EVs in urban city. However, the limited battery volume of EV certainly influences its driver's experience. This is mainly because the EV needed for intermediate charging during trip, may experience a long service waiting time at Charging Station (CS). In this paper, we focus on CS-selection decision making to manage EVs' charging plans, aiming to minimize drivers' trip duration through intermediate charging at CSs. The anticipated EVs' charging reservations including their arrival time and expected charging time at CSs, are brought for charging management, in addition to taking the local status of CSs into account. Compared to applying traditionally applying cellular network communication to report EVs' charging reservations, we alternatively study the feasibility of applying Vehicle-to-Vehicle (V2V) communication with Delay/Disruption Tolerant Networking (DTN) nature, due primarily to its flexibility and cost-efficiency in Vehicular Ad hoc NETworks (VANETs). Evaluation results under the realistic Helsinki city scenario show that applying the V2V for reservation reporting is promisingly cost-efficient in terms of communication overhead for reservation making, while achieving a comparable performance in terms of charging waiting time and total trip duration.Index Terms-Electric Vehicle, Charging Management, Vehicle-to-Vehicle Communication.

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Section: A Research On Ev Charging Managementmentioning

confidence: 99%

“…This means the EV with an earlier arrival will be scheduled with a higher priority. Note that the FCFS policy has been widely applied by previous works [5]- [7] on CS-selection problem.…”

Section: B System Cycle Of Ev Charging Managementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Applying DTN routing for reservation-driven EV Charging management in smart cities

Cao

Zhang

Wang

et al. 2017

2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC)

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“…Moreover, charging facilities are typically limited and must therefore be used efficiently [35]. In [36], an integrated rapid charging navigation strategy is presented that considers both traffic conditions and the status of power grids. Other studies propose solutions for charging autonomous EVs in parking places and using scarce charging facilities more efficiently, thus simplifying the life of customers and increasing the feasibility of EVs [37,38].…”

Section: Introductionmentioning

confidence: 99%

The Concept of EV’s Intelligent Integrated Station and Its Energy Flow

et al. 2015

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Abstract:The increasing number of electric vehicles (EVs) connected to existing distribution networks as time-variant loads cause significant distortions in line current and voltage. A novel EV's intelligent integrated station (IIS) making full use of retired batteries is introduced in this paper to offer a potential solution for accommodating the charging demand of EVs. It proposes the concept of generalized energy in IIS, based on the energy/power flow between IIS and EVs, and between IIS and the power grid, to systematically evaluate the energy capacity of IIS. In order to derive a unique and satisfactory operation mode, information from both the grid (in terms of load level) and IIS (in terms of its energy capacity and EVs battery charging/exchanging requests) is merged. Then, based on the generalized energy of different systems, a novel charging/discharging control strategy is presented and whereby the operating status of the grid and energy capacity of IIS are monitored to make reasonable operation plans for IIS. Simulation results suggest that the proposed IIS offers peak load shifting when EV battery charging/exchanging requests are satisfied compared to existing charging stations. OPEN ACCESSEnergies 2015, 8 4189

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“…Furthermore, recent literature has focused on developing strategies for navigating the consumers to find the more suitable power delivery for EV charging [9]; using energy storage and the electricity market to manage the EV charging is also investigated [10]; using aggregators to manage the impact to the grid is also explores [11].…”

mentioning

confidence: 99%

Controlled Electric Vehicle Charging for Mitigating Impacts on Distribution Assets

Aravinthan

Jewell

2015

IEEE Trans. Smart Grid

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This paper proposes a two-step methodology for scheduling electric vehicle (EV) charging, which limits the burden on distribution and transmission assets while ensuring all the vehicles are charged. In the first step, the number of vehicles to be charged during each hour is optimized based on day-ahead requests for charging. The second step determines the maximum number of vehicles that can be charged based on operating conditions during the next hour to ensure distribution reliability requirements are met. A numerical example is given to illustrate the EV charging management scheme. This technique will limit the effects of EV charging on distribution assets.Index Terms-Distribution system, electric vehicles (EVs) charging, greenhouse gas (GHG) emission, loss of life (LOL) of components reliability.

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Rapid-Charging Navigation of Electric Vehicles Based on Real-Time Power Systems and Traffic Data

Cited by 155 publications

References 40 publications

Applying DTN routing for reservation-driven EV Charging management in smart cities

Applying DTN routing for reservation-driven EV Charging management in smart cities

The Concept of EV’s Intelligent Integrated Station and Its Energy Flow

Controlled Electric Vehicle Charging for Mitigating Impacts on Distribution Assets

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