Optimal user oriented multi-level experience planning strategy for electric automobile charging path

Focusing on the battery-charging problem that is brought to the electric automobile users, this paper integrated the “automobile-network-path” multi-source information and presented the multi-level user experience index system which combined charging prices, driving distances, degrees of traffic con...

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Main Authors: Wang Wen, Peng Xiaofeng, Jia Jun, Zhao Ji, Xiao Wei, Su Shu
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/78/e3sconf_iseese2020_02028.pdf
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spelling doaj-c69bbedf4f26453f8a50b99f751175bd2021-04-02T16:02:26ZengEDP SciencesE3S Web of Conferences2267-12422020-01-012180202810.1051/e3sconf/202021802028e3sconf_iseese2020_02028Optimal user oriented multi-level experience planning strategy for electric automobile charging pathWang Wen0Peng Xiaofeng1Jia Jun2Zhao Ji3Xiao Wei4Su Shu5State Grid Electric Vehicle Service Co., Ltd.State Grid Electric Vehicle Service Co., Ltd.Tsinghua Sichuan Energy Internet Research InstituteTsinghua Sichuan Energy Internet Research InstituteTsinghua Sichuan Energy Internet Research InstituteState Grid Electric Vehicle Service Co., Ltd.Focusing on the battery-charging problem that is brought to the electric automobile users, this paper integrated the “automobile-network-path” multi-source information and presented the multi-level user experience index system which combined charging prices, driving distances, degrees of traffic congestion and other factors. The recommended algorithm and model for charging strategy was built up to improve the user experience. Meanwhile, it invoked map Application Programming Interface (API) to plan multiple paths. Consolidated by the status of charging piles, the distance between the automobile and the piles, the charging prices along with more real-time information, the multi-level user oriented experience index system was set up to recommend an optimal navigation route to the charging station for the automobile owners. Validated by the application results, the proposed algorithm that helped navigate to the charging stations or piles can effectively solve the practical problems1 such as difficulty in orienting the charging piles, waiting in lines, and high charging fees.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/78/e3sconf_iseese2020_02028.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Wang Wen
Peng Xiaofeng
Jia Jun
Zhao Ji
Xiao Wei
Su Shu
spellingShingle Wang Wen
Peng Xiaofeng
Jia Jun
Zhao Ji
Xiao Wei
Su Shu
Optimal user oriented multi-level experience planning strategy for electric automobile charging path
E3S Web of Conferences
author_facet Wang Wen
Peng Xiaofeng
Jia Jun
Zhao Ji
Xiao Wei
Su Shu
author_sort Wang Wen
title Optimal user oriented multi-level experience planning strategy for electric automobile charging path
title_short Optimal user oriented multi-level experience planning strategy for electric automobile charging path
title_full Optimal user oriented multi-level experience planning strategy for electric automobile charging path
title_fullStr Optimal user oriented multi-level experience planning strategy for electric automobile charging path
title_full_unstemmed Optimal user oriented multi-level experience planning strategy for electric automobile charging path
title_sort optimal user oriented multi-level experience planning strategy for electric automobile charging path
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2020-01-01
description Focusing on the battery-charging problem that is brought to the electric automobile users, this paper integrated the “automobile-network-path” multi-source information and presented the multi-level user experience index system which combined charging prices, driving distances, degrees of traffic congestion and other factors. The recommended algorithm and model for charging strategy was built up to improve the user experience. Meanwhile, it invoked map Application Programming Interface (API) to plan multiple paths. Consolidated by the status of charging piles, the distance between the automobile and the piles, the charging prices along with more real-time information, the multi-level user oriented experience index system was set up to recommend an optimal navigation route to the charging station for the automobile owners. Validated by the application results, the proposed algorithm that helped navigate to the charging stations or piles can effectively solve the practical problems1 such as difficulty in orienting the charging piles, waiting in lines, and high charging fees.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/78/e3sconf_iseese2020_02028.pdf
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