Comprehensive QoS Analysis of Urban Public Charging Network in Topology and Capacity With Its Application in Optimization

Booming electric vehicles (EVs) lead to degraded quality-of-service (QoS) of urban public charging network (UPCN) consisting of public charging stations (PCSs) and traffic network, such as prolonged waiting time at popular PCSs. UPCN QoS analysis creates broad prospects in QoS optimization by provid...

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Main Authors: Jing Fu, Liyu Lin, Xun Gao
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9026872/
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spelling doaj-d580c05fb60549dca0e94d5ce6d8c3372021-03-30T03:11:21ZengIEEEIEEE Access2169-35362020-01-018536365364810.1109/ACCESS.2020.29789059026872Comprehensive QoS Analysis of Urban Public Charging Network in Topology and Capacity With Its Application in OptimizationJing Fu0https://orcid.org/0000-0003-1720-7641Liyu Lin1https://orcid.org/0000-0002-5453-8717Xun Gao2https://orcid.org/0000-0002-3344-1860Electronic Information School, Wuhan University, Wuhan, ChinaState Key Laboratory of Surveying and Mapping Remote Sensing Information Engineering, Wuhan University, Wuhan, ChinaElectronic Information School, Wuhan University, Wuhan, ChinaBooming electric vehicles (EVs) lead to degraded quality-of-service (QoS) of urban public charging network (UPCN) consisting of public charging stations (PCSs) and traffic network, such as prolonged waiting time at popular PCSs. UPCN QoS analysis creates broad prospects in QoS optimization by providing reliable tools to improve UPCN performance. Conventional methods focusing on the impact of network topology on QoS underestimates effects of network capacity and its distribution among PCSs. In this paper, we proposed a heterogeneous UPCN model with limited PCS service capacity, and constructed a QoS analysis method according to PCS and EV characteristics from classic method for traffic assignment model, in which we analyzed waiting time at PCSs by queueing theory and calculated feasible routes for EVs recharging half-way by screening from deep-first-search results. Finally, we demonstrated an application of the proposed model and method in QoS optimization. We carried out experiments on popular Sioux Falls network with randomly-added PCSs. Results indicate that proportion of traditionally neglected waiting time at PCSs may reach 22% in EVs' total travel time if fast charging piles serve 2 vehicles/h, and the gap between our method and conventional method in average waiting time and spatial throughput distribution is growing as EV amount increases. These results support our method's advantages in simulating EVs' charging choice trade-off between farther routes and popular PCSs as well as higher performance in UPCN QoS optimization.https://ieeexplore.ieee.org/document/9026872/Charging networkelectric vehiclesqueueing analysistraffic control
collection DOAJ
language English
format Article
sources DOAJ
author Jing Fu
Liyu Lin
Xun Gao
spellingShingle Jing Fu
Liyu Lin
Xun Gao
Comprehensive QoS Analysis of Urban Public Charging Network in Topology and Capacity With Its Application in Optimization
IEEE Access
Charging network
electric vehicles
queueing analysis
traffic control
author_facet Jing Fu
Liyu Lin
Xun Gao
author_sort Jing Fu
title Comprehensive QoS Analysis of Urban Public Charging Network in Topology and Capacity With Its Application in Optimization
title_short Comprehensive QoS Analysis of Urban Public Charging Network in Topology and Capacity With Its Application in Optimization
title_full Comprehensive QoS Analysis of Urban Public Charging Network in Topology and Capacity With Its Application in Optimization
title_fullStr Comprehensive QoS Analysis of Urban Public Charging Network in Topology and Capacity With Its Application in Optimization
title_full_unstemmed Comprehensive QoS Analysis of Urban Public Charging Network in Topology and Capacity With Its Application in Optimization
title_sort comprehensive qos analysis of urban public charging network in topology and capacity with its application in optimization
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description Booming electric vehicles (EVs) lead to degraded quality-of-service (QoS) of urban public charging network (UPCN) consisting of public charging stations (PCSs) and traffic network, such as prolonged waiting time at popular PCSs. UPCN QoS analysis creates broad prospects in QoS optimization by providing reliable tools to improve UPCN performance. Conventional methods focusing on the impact of network topology on QoS underestimates effects of network capacity and its distribution among PCSs. In this paper, we proposed a heterogeneous UPCN model with limited PCS service capacity, and constructed a QoS analysis method according to PCS and EV characteristics from classic method for traffic assignment model, in which we analyzed waiting time at PCSs by queueing theory and calculated feasible routes for EVs recharging half-way by screening from deep-first-search results. Finally, we demonstrated an application of the proposed model and method in QoS optimization. We carried out experiments on popular Sioux Falls network with randomly-added PCSs. Results indicate that proportion of traditionally neglected waiting time at PCSs may reach 22% in EVs' total travel time if fast charging piles serve 2 vehicles/h, and the gap between our method and conventional method in average waiting time and spatial throughput distribution is growing as EV amount increases. These results support our method's advantages in simulating EVs' charging choice trade-off between farther routes and popular PCSs as well as higher performance in UPCN QoS optimization.
topic Charging network
electric vehicles
queueing analysis
traffic control
url https://ieeexplore.ieee.org/document/9026872/
work_keys_str_mv AT jingfu comprehensiveqosanalysisofurbanpublicchargingnetworkintopologyandcapacitywithitsapplicationinoptimization
AT liyulin comprehensiveqosanalysisofurbanpublicchargingnetworkintopologyandcapacitywithitsapplicationinoptimization
AT xungao comprehensiveqosanalysisofurbanpublicchargingnetworkintopologyandcapacitywithitsapplicationinoptimization
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