Charging optimization of battery electric vehicles including cycle battery aging

Annette E. Trippe; Raghavendra Arunachala; Tobias Massier; Andreas Jossen; Thomas Hamacher

doi:10.1109/ISGTEurope.2014.7028735

Charging optimization of battery electric vehicles including cycle battery aging

Annette E. Trippe
, Raghavendra Arunachala
, Tobias Massier
, Andreas Jossen
, Thomas Hamacher

TUM CREATE

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

14 Scopus citations

Abstract

Controlled charging of battery electric vehicles is one instrument of smart grids in order to intelligently use the electricity load generated by electric vehicles (EVs). However, battery constraints as well as effects of the charging processes on the battery should not be neglected. This work elaborates an EV charging model, which optimizes the charging process while considering cycle battery aging effects. Formulated as a quadratic constraint program, it minimizes total charging cost, consisting of charging electricity cost and battery aging cost. Cycle battery aging tests are conducted and used to analyze and model the battery aging behavior. The optimization model is applied to a sample of EVs in Singapore and four different scenarios are evaluated. The resulting battery aging cost accounts for a substantial share of the total charging cost, i.e., between 52% and 93%. Therefore, an inclusion of battery aging into the intelligent controlling of EV charging is crucial.

Original language	English
Title of host publication	2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014
Publisher	IEEE Computer Society
Edition	January
ISBN (Electronic)	9781479977208
DOIs	https://doi.org/10.1109/ISGTEurope.2014.7028735
State	Published - 30 Jan 2015
Event	2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014 - Istanbul, Turkey Duration: 12 Oct 2014 → 15 Oct 2014

Publication series

Name	IEEE PES Innovative Smart Grid Technologies Conference Europe
Number	January
Volume	2015-January

Conference

Conference	2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014
Country/Territory	Turkey
City	Istanbul
Period	12/10/14 → 15/10/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Cost optimization
Cycle battery aging
Electric vehicles
Intelligent charging

Access to Document

10.1109/ISGTEurope.2014.7028735

Cite this

Trippe, A. E., Arunachala, R., Massier, T., Jossen, A., & Hamacher, T. (2015). Charging optimization of battery electric vehicles including cycle battery aging. In 2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014 (January ed.). Article 7028735 (IEEE PES Innovative Smart Grid Technologies Conference Europe; Vol. 2015-January, No. January). IEEE Computer Society. https://doi.org/10.1109/ISGTEurope.2014.7028735

@inproceedings{e8b7017a93e349a6bab534fa19f4c96d,

title = "Charging optimization of battery electric vehicles including cycle battery aging",

abstract = "Controlled charging of battery electric vehicles is one instrument of smart grids in order to intelligently use the electricity load generated by electric vehicles (EVs). However, battery constraints as well as effects of the charging processes on the battery should not be neglected. This work elaborates an EV charging model, which optimizes the charging process while considering cycle battery aging effects. Formulated as a quadratic constraint program, it minimizes total charging cost, consisting of charging electricity cost and battery aging cost. Cycle battery aging tests are conducted and used to analyze and model the battery aging behavior. The optimization model is applied to a sample of EVs in Singapore and four different scenarios are evaluated. The resulting battery aging cost accounts for a substantial share of the total charging cost, i.e., between 52\% and 93\%. Therefore, an inclusion of battery aging into the intelligent controlling of EV charging is crucial.",

keywords = "Cost optimization, Cycle battery aging, Electric vehicles, Intelligent charging",

author = "Trippe, \{Annette E.\} and Raghavendra Arunachala and Tobias Massier and Andreas Jossen and Thomas Hamacher",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014 ; Conference date: 12-10-2014 Through 15-10-2014",

year = "2015",

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Trippe, AE, Arunachala, R, Massier, T, Jossen, A & Hamacher, T 2015, Charging optimization of battery electric vehicles including cycle battery aging. in 2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014. January edn, 7028735, IEEE PES Innovative Smart Grid Technologies Conference Europe, no. January, vol. 2015-January, IEEE Computer Society, 2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014, Istanbul, Turkey, 12/10/14. https://doi.org/10.1109/ISGTEurope.2014.7028735

Charging optimization of battery electric vehicles including cycle battery aging. / Trippe, Annette E.; Arunachala, Raghavendra; Massier, Tobias et al.
2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014. January. ed. IEEE Computer Society, 2015. 7028735 (IEEE PES Innovative Smart Grid Technologies Conference Europe; Vol. 2015-January, No. January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Charging optimization of battery electric vehicles including cycle battery aging

AU - Trippe, Annette E.

AU - Arunachala, Raghavendra

AU - Massier, Tobias

AU - Jossen, Andreas

AU - Hamacher, Thomas

PY - 2015/1/30

Y1 - 2015/1/30

N2 - Controlled charging of battery electric vehicles is one instrument of smart grids in order to intelligently use the electricity load generated by electric vehicles (EVs). However, battery constraints as well as effects of the charging processes on the battery should not be neglected. This work elaborates an EV charging model, which optimizes the charging process while considering cycle battery aging effects. Formulated as a quadratic constraint program, it minimizes total charging cost, consisting of charging electricity cost and battery aging cost. Cycle battery aging tests are conducted and used to analyze and model the battery aging behavior. The optimization model is applied to a sample of EVs in Singapore and four different scenarios are evaluated. The resulting battery aging cost accounts for a substantial share of the total charging cost, i.e., between 52% and 93%. Therefore, an inclusion of battery aging into the intelligent controlling of EV charging is crucial.

AB - Controlled charging of battery electric vehicles is one instrument of smart grids in order to intelligently use the electricity load generated by electric vehicles (EVs). However, battery constraints as well as effects of the charging processes on the battery should not be neglected. This work elaborates an EV charging model, which optimizes the charging process while considering cycle battery aging effects. Formulated as a quadratic constraint program, it minimizes total charging cost, consisting of charging electricity cost and battery aging cost. Cycle battery aging tests are conducted and used to analyze and model the battery aging behavior. The optimization model is applied to a sample of EVs in Singapore and four different scenarios are evaluated. The resulting battery aging cost accounts for a substantial share of the total charging cost, i.e., between 52% and 93%. Therefore, an inclusion of battery aging into the intelligent controlling of EV charging is crucial.

KW - Cost optimization

KW - Cycle battery aging

KW - Electric vehicles

KW - Intelligent charging

UR - https://www.scopus.com/pages/publications/84936972737

U2 - 10.1109/ISGTEurope.2014.7028735

DO - 10.1109/ISGTEurope.2014.7028735

M3 - Conference contribution

AN - SCOPUS:84936972737

T3 - IEEE PES Innovative Smart Grid Technologies Conference Europe

BT - 2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014

PB - IEEE Computer Society

T2 - 2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014

Y2 - 12 October 2014 through 15 October 2014

ER -

Trippe AE, Arunachala R, Massier T, Jossen A , Hamacher T. Charging optimization of battery electric vehicles including cycle battery aging. In 2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014. January ed. IEEE Computer Society. 2015. 7028735. (IEEE PES Innovative Smart Grid Technologies Conference Europe; January). doi: 10.1109/ISGTEurope.2014.7028735

Charging optimization of battery electric vehicles including cycle battery aging

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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