Identification of EV use patterns, based on large scale EV monitoring data

C. De Cauwer; D. Gillis; T. Coosemans; J. Van Mierlo

doi:10.1109/EVS.2013.6915044

Identification of EV use patterns, based on large scale EV monitoring data

C. De Cauwer, D. Gillis, T. Coosemans, J. Van Mierlo

Onderzoeksoutput: Conference paper

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This paper presents a methodology to analyse electric vehicle (EV) monitoring data to identify use patterns. The methodology is applied to the monitored data of a fleet of electric vehicles and plug-in hybrid vehicles (PHEV). The methodology introduces a link of the travel behaviour and characterisation with the range of the electric vehicle. To identify use patterns a number of indicators are defined: reset points, extra range potential, daily distance driven, average distance between reset points and maximum distance between two reset points. These indicators are calculated on monitored data of EVs, and the first results and observations are presented.

Originele taal-2	English
Titel	2013 World Electric Vehicle Symposium and Exhibition, EVS 2014
Uitgeverij	Institute of Electrical and Electronics Engineers Inc.
Pagina's	1-11
ISBN van elektronische versie	9781479938322
DOI's	https://doi.org/10.1109/EVS.2013.6915044
Status	Published - 1 okt 2014
Evenement	27th World Electric Vehicle Symposium and Exhibition, EVS 2014 - Barcelona, Spain Duur: 17 nov 2013 → 20 nov 2013

Conference

Conference	27th World Electric Vehicle Symposium and Exhibition, EVS 2014
Land/Regio	Spain
Stad	Barcelona
Periode	17/11/13 → 20/11/13

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EVS27 full paper - Identification of EV use patters based on large scale monitoring data

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title = "Identification of EV use patterns, based on large scale EV monitoring data",

abstract = "This paper presents a methodology to analyse electric vehicle (EV) monitoring data to identify use patterns. The methodology is applied to the monitored data of a fleet of electric vehicles and plug-in hybrid vehicles (PHEV). The methodology introduces a link of the travel behaviour and characterisation with the range of the electric vehicle. To identify use patterns a number of indicators are defined: reset points, extra range potential, daily distance driven, average distance between reset points and maximum distance between two reset points. These indicators are calculated on monitored data of EVs, and the first results and observations are presented.",

keywords = "BEV(battery electric vehicle), mobility, range",

author = "{De Cauwer}, C. and D. Gillis and T. Coosemans and {Van Mierlo}, J.",

year = "2014",

month = oct,

day = "1",

doi = "10.1109/EVS.2013.6915044",

language = "English",

pages = "1--11",

booktitle = "2013 World Electric Vehicle Symposium and Exhibition, EVS 2014",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "27th World Electric Vehicle Symposium and Exhibition, EVS 2014 ; Conference date: 17-11-2013 Through 20-11-2013",

}

De Cauwer, C, Gillis, D, Coosemans, T & Van Mierlo, J 2014, Identification of EV use patterns, based on large scale EV monitoring data. in 2013 World Electric Vehicle Symposium and Exhibition, EVS 2014., 6915044, Institute of Electrical and Electronics Engineers Inc., blz. 1-11, 27th World Electric Vehicle Symposium and Exhibition, EVS 2014, Barcelona, Spain, 17/11/13. https://doi.org/10.1109/EVS.2013.6915044

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AU - Coosemans, T.

AU - Van Mierlo, J.

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N2 - This paper presents a methodology to analyse electric vehicle (EV) monitoring data to identify use patterns. The methodology is applied to the monitored data of a fleet of electric vehicles and plug-in hybrid vehicles (PHEV). The methodology introduces a link of the travel behaviour and characterisation with the range of the electric vehicle. To identify use patterns a number of indicators are defined: reset points, extra range potential, daily distance driven, average distance between reset points and maximum distance between two reset points. These indicators are calculated on monitored data of EVs, and the first results and observations are presented.

AB - This paper presents a methodology to analyse electric vehicle (EV) monitoring data to identify use patterns. The methodology is applied to the monitored data of a fleet of electric vehicles and plug-in hybrid vehicles (PHEV). The methodology introduces a link of the travel behaviour and characterisation with the range of the electric vehicle. To identify use patterns a number of indicators are defined: reset points, extra range potential, daily distance driven, average distance between reset points and maximum distance between two reset points. These indicators are calculated on monitored data of EVs, and the first results and observations are presented.

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Identification of EV use patterns, based on large scale EV monitoring data

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