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
N1 - Publisher Copyright:
© 2014 IEEE.
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 - http://www.scopus.com/inward/record.url?scp=84936972737&partnerID=8YFLogxK
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 -