Electric-Vehicle Navigation System Based on Power Consumption.
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| Title: | Electric-Vehicle Navigation System Based on Power Consumption. |
|---|---|
| Authors: | Yang, Jyun-Yan1, Chou, Li-Der1, Chang, Yao-Jen2 |
| Source: | IEEE Transactions on Vehicular Technology. Aug2016, Vol. 65 Issue 8, p5930-5943. 14p. |
| Subjects: | Electric vehicles, Automotive navigation systems, Electric power consumption, Global warming, Electric vehicle charging stations, Equipment & supplies |
| Abstract: | Electric vehicles will become a popular mode of travel when petroleum prices increase and global warming intensifies. However, the short driving range of electric vehicles remains a challenge. To avoid battery depletion, navigation systems route electric vehicles to surrounding charging stations for battery exchange or recharge. Nonetheless, zero inventories and occupied sockets may result in variable charging time and longer travel time. Conventional navigation approaches have been unable to respond to variable charging time because these approaches do not consider the charging times and energy consumption of electric vehicles. Navigation systems can manage shared information, traffic, and battery life, and can improve the mileage per kilowatthour of electric vehicles. In this paper, an electric-vehicle navigation system (EVNS) based on an autonomic computing architecture and a hierarchical architecture over vehicular ad-hoc networks (VANETs) is proposed. In addition to moving energy, the proposed EVNS considers air conditioner energy to predict the state of charge (SOC) because air conditioning is the most demanding auxiliary load in electric vehicles. Moreover, this paper proposes a time-dependent routing algorithm that considers shared information. The results show that the proposed EVNS method results in 31.15% and 9.52% improvements in mileage compared with the shortest path first (SPF) method and the distributed method in Manhattan, New York City, NY, USA, respectively. Furthermore, the proposed EVNS method results in 32.39% and 20.67% improvements in mileage compared with the SPF method and the distributed method in Taipei, Taiwan, respectively. [ABSTRACT FROM AUTHOR] |
| Copyright of IEEE Transactions on Vehicular Technology is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 117445621 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Electric-Vehicle Navigation System Based on Power Consumption. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yang%2C+Jyun-Yan%22">Yang, Jyun-Yan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chou%2C+Li-Der%22">Chou, Li-Der</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chang%2C+Yao-Jen%22">Chang, Yao-Jen</searchLink><relatesTo>2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Vehicular+Technology%22">IEEE Transactions on Vehicular Technology</searchLink>. Aug2016, Vol. 65 Issue 8, p5930-5943. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Electric+vehicles%22">Electric vehicles</searchLink><br /><searchLink fieldCode="DE" term="%22Automotive+navigation+systems%22">Automotive navigation systems</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+power+consumption%22">Electric power consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Global+warming%22">Global warming</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+vehicle+charging+stations%22">Electric vehicle charging stations</searchLink><br /><searchLink fieldCode="DE" term="%22Equipment+%26+supplies%22">Equipment & supplies</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Electric vehicles will become a popular mode of travel when petroleum prices increase and global warming intensifies. However, the short driving range of electric vehicles remains a challenge. To avoid battery depletion, navigation systems route electric vehicles to surrounding charging stations for battery exchange or recharge. Nonetheless, zero inventories and occupied sockets may result in variable charging time and longer travel time. Conventional navigation approaches have been unable to respond to variable charging time because these approaches do not consider the charging times and energy consumption of electric vehicles. Navigation systems can manage shared information, traffic, and battery life, and can improve the mileage per kilowatthour of electric vehicles. In this paper, an electric-vehicle navigation system (EVNS) based on an autonomic computing architecture and a hierarchical architecture over vehicular ad-hoc networks (VANETs) is proposed. In addition to moving energy, the proposed EVNS considers air conditioner energy to predict the state of charge (SOC) because air conditioning is the most demanding auxiliary load in electric vehicles. Moreover, this paper proposes a time-dependent routing algorithm that considers shared information. The results show that the proposed EVNS method results in 31.15% and 9.52% improvements in mileage compared with the shortest path first (SPF) method and the distributed method in Manhattan, New York City, NY, USA, respectively. Furthermore, the proposed EVNS method results in 32.39% and 20.67% improvements in mileage compared with the SPF method and the distributed method in Taipei, Taiwan, respectively. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IEEE Transactions on Vehicular Technology is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1109/TVT.2015.2477369 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 5930 Subjects: – SubjectFull: Electric vehicles Type: general – SubjectFull: Automotive navigation systems Type: general – SubjectFull: Electric power consumption Type: general – SubjectFull: Global warming Type: general – SubjectFull: Electric vehicle charging stations Type: general – SubjectFull: Equipment & supplies Type: general Titles: – TitleFull: Electric-Vehicle Navigation System Based on Power Consumption. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yang, Jyun-Yan – PersonEntity: Name: NameFull: Chou, Li-Der – PersonEntity: Name: NameFull: Chang, Yao-Jen IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2016 Type: published Y: 2016 Identifiers: – Type: issn-print Value: 00189545 Numbering: – Type: volume Value: 65 – Type: issue Value: 8 Titles: – TitleFull: IEEE Transactions on Vehicular Technology Type: main |
| ResultId | 1 |
