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Modeling and data analysis of electric vehicle fleet charging.

Kucuksari, Sadik; Erdogan, Nuh

Authors

Sadik Kucuksari



Abstract

In the transition to electric fleets around the world, electricity demand from electric vehicle (EV) fleets is expected to become significant in the future. Since fleet cars can display different charging characteristics than individual EVs, analyzing the charging behavior patterns of fleet cars is essential. To do so, this study first examines real EV fleet data from 724 charging events using data analytics methods. Based on this analysis, a charging behavior model is then developed to predict the realistic charging demand of an EV fleet with any number of EVs. In order to overcome the limitations of traditional probability density functions, this study utilizes Gaussian Mixture Models and Kernel distribution in developing charging behaviour models, i.e., charging start and end times, and total charging energy. The models' behaviours are then compared in terms of goodness-of-fit (GoF) to determine the best match for the original data, in which normalised root mean squared error serving as the fitness criteria.

Citation

KUCUKSARI, S. and ERDOGAN, N. 2022. Modeling and data analysis of electric vehicle fleet charging. In Proceedings of 2022 IEEE (Institute of Electrical and Electronics Engineers)/AIAA (American Institute of Aeronautics and Astronautics) Transportation electrification conference and Electric aircraft technologies symposium (ITEC+EATS), 15-17 June 2022, Anaheim, USA. Piscataway: IEEE [online], pages 1139-1143. Available from: https://doi.org/10.1109/itec53557.2022.9814047

Conference Name 2022 IEEE IEEE (Institute of Electrical and Electronics Engineers)/AIAA (American Institute of Aeronautics and Astronautics) Transportation electrification conference and Electric aircraft technologies symposium (ITEC+EATS)
Conference Location Anaheim, CA, USA
Start Date Jun 15, 2022
End Date Jun 17, 2022
Acceptance Date Feb 28, 2022
Online Publication Date Jun 17, 2022
Publication Date Jul 2, 2022
Deposit Date Aug 2, 2022
Publicly Available Date Aug 2, 2022
Publisher IEEE Institute of Electrical and Electronics Engineers
Pages 1139-1143
Book Title Proceedings of 2022 IEEE (Institute of Electrical and Electronics Engineers)/AIAA (American Institute of Aeronautics and Astronautics) Transportation electrification conference and Electric aircraft technologies symposium (ITEC+EATS)
ISBN 9781665405607
DOI https://doi.org/10.1109/ITEC53557.2022.9814047
Keywords Data analytics; Electrified fleets; Fleet charging; Gaussian mixture model; Kernel distribution; Plug-in electric vehicles; Probability density functions
Public URL https://rgu-repository.worktribe.com/output/1713048

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