Charge scheduling of electric vehicles in highways

Yang, Shun Neng; Cheng, Wanli; Hsu, Yuan-Ming; Gan, Chai Hien; Lin, Yi

doi:10.1016/j.mcm.2011.11.054

Cited by 110 publications

(51 citation statements)

References 7 publications

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“…The works in [5], [7], [9] estimate the queuing time at CSs, such that the one with the minimum queueing time is ranked as the best charging option. The work in [3] compares the schemes to select CS based on either the closest distance or minimum waiting time, where results show that the latter performs better given high EVs density under city scenario.…”

Section: B Electro-mobility For Where To Chargementioning

confidence: 99%

Toward Anycasting-Driven Reservation System for Electric Vehicle Battery Switch Service

Cao

Wang

Zhang

et al. 2019

IEEE Systems Journal

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Abstract-Electro-Mobility has become an increasingly important research problem in urban city. Due to the limited electricity of battery, Electric Vehicle (EV) drivers may experience discomfort for long charging waiting time. Different from plug-in charging technology, we investigate the battery switch technology to improve EV drivers' comfort (e.g., reduce the service waiting time from tens of minutes to a few minutes), by benefiting from switchable (fully-recharged) batteries cycled at Charging Stations (CSs). Since demand hotspot may still happen at CSs (e.g., running out of switchable batteries), incoming EVs may wait additional time to get their battery switched, and thus the EV driver's comfort is degraded. Firstly, we propose a centralized reservation enabling service, considering EVs' reservations (including arrival time, expected charging time of their batteries to be depleted) to optimally coordinate their battery switch plans. Secondly, a decentralized system is further proposed, by facilitating the Vehicle-to-Vehicle (V2V) anycasting to deliver EV's reservations. This helps to address some of the privacy issues that can be materialized in centralized system and reduce communication cost (e.g., through cellular network for reservation making). Results under the Helsinki city scenario show a trade-off between comparable performance (e.g., service waiting time, number of switched batteries) and cellular network cost for EVs' reservations delivery.

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Section: B Electro-mobility For Where To Chargementioning

confidence: 99%

Toward Anycasting-Driven Reservation System for Electric Vehicle Battery Switch Service

Cao

Wang

Zhang

et al. 2019

IEEE Systems Journal

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“…Generally, there are several service areas in per node or main road segment, but these adjacent service areas of the node can be combined into a single service area in this paper. We assume that one CS is located at per selected service area [11]. Therefore, a total of 58 CSs can be set up in the simplified expressway network according to the location of per service area and the distribution of the CSs in the network is shown in Figure 5.…”

Section: Distribution and Capacity Allocation Of Charging Stations Inmentioning

confidence: 99%

A Study on Price-Based Charging Strategy for Electric Vehicles on Expressways

et al. 2016

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Abstract:With the large-scale adoption of electric vehicles (EVs) on expressways, the exploration of a guiding-based charging method to effectively adjust interactions between EVs and the fast charging stations (CSs) is urgently needed. This paper proposes a status-of-use (SOU) price-based charging strategy that can motivate users to charge in advance. A queuing model for a CS cluster was established to verify the effectiveness of the strategy, and then a simulation of traveling and charging conditions of 12,000 pure EVs on the road network from 0:00 to 24:00 was performed according to the related data and using the Monte Carlo method, the Floyd-Warshall algorithm, and the queuing algorithm proposed in this paper. Compared to unordered charging (UC), SOU price-based charging can not only reduce the charging cost and waiting time for users, but also increase the utilization ratio of charging facilities in a CS cluster and thus lower their influence on the power grid and expressway traffic. SOU price-based charging can effectively adjust interactions between EVs and CSs.

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“…A few previous works [6]- [9] have addressed CS-selection decision making to minimize the EVs' charging waiting time, by monitoring the local status of CSs. Basically, the CS with the highest availability (e.g., minimum queuing time [9]) will be selected as the best choice.…”

Section: Introductionmentioning

confidence: 99%

“…In the latter branch, the works in [6], [9] estimate the queuing time at CSs, such that the one with the minimum queueing time is ranked as the best charging option. The work in [7] compares the schemes to select CS based either on the closest distance or minimum waiting time, where results show that the latter performs better given high EVs density under city scenario.…”

Section: Introductionmentioning

confidence: 99%

An EV Charging Management System Concerning Drivers’ Trip Duration and Mobility Uncertainty

Cao

Wang

Kaiwartya

et al. 2018

IEEE Trans. Syst. Man Cybern, Syst.

150

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Abstract-With continually increased attention on Electric Vehicles (EVs) due to environment impact, public Charging Stations (CSs) for EVs will become common. However, due to the limited electricity of battery, EV drivers may experience discomfort for long charging waiting time during their journeys. This often happens when a large number of (on-the-move) EVs are planning to charge at the same CS, but it has been heavily overloaded. With this concern, in an EV charging management system, we focus on CS-selection decision making and propose a scheme to manage EVs' charging plans, to minimize drivers' trip duration through intermediate charging at CSs. The proposed scheme jointly considers EVs' anticipated charging reservations (including arrival time, expected charging time) and parking duration at CSs. Furthermore, by tackling mobility uncertainty that EVs may not reach their planned CSs on time (due to traffic jams on the road), a periodical reservation updating mechanism is designed to adjust their charging plans. Results under the Helsinki city scenario with realistic EV and CS characteristics show the advantage of our proposal, in terms of minimized drivers' trip duration, as well as charging performance at the EV and CS sides.

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Charge scheduling of electric vehicles in highways

Cited by 110 publications

References 7 publications

Toward Anycasting-Driven Reservation System for Electric Vehicle Battery Switch Service

Toward Anycasting-Driven Reservation System for Electric Vehicle Battery Switch Service

A Study on Price-Based Charging Strategy for Electric Vehicles on Expressways

An EV Charging Management System Concerning Drivers’ Trip Duration and Mobility Uncertainty

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