Home > Research > Publications & Outputs > A Coordinated Battery Swapping Service Manageme...

Electronic data

  • FINAL VERSION

    Accepted author manuscript, 3.1 MB, PDF document

    Available under license: CC BY: Creative Commons Attribution 4.0 International License

Links

Text available via DOI:

View graph of relations

A Coordinated Battery Swapping Service Management Scheme Based on Battery Heterogeneity

Research output: Contribution to Journal/MagazineJournal articlepeer-review

E-pub ahead of print

Standard

A Coordinated Battery Swapping Service Management Scheme Based on Battery Heterogeneity. / Li, Xinyu; Cao, Yue; Wan, Shaohua et al.
In: IEEE Transactions on Transportation Electrification, Vol. 9, No. 3, 13.02.2023, p. 4474-4491.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Li, X, Cao, Y, Wan, S, Liu, S, Lin, H & Zhu, Y 2023, 'A Coordinated Battery Swapping Service Management Scheme Based on Battery Heterogeneity', IEEE Transactions on Transportation Electrification, vol. 9, no. 3, pp. 4474-4491. https://doi.org/10.1109/tte.2023.3244580

APA

Li, X., Cao, Y., Wan, S., Liu, S., Lin, H., & Zhu, Y. (2023). A Coordinated Battery Swapping Service Management Scheme Based on Battery Heterogeneity. IEEE Transactions on Transportation Electrification, 9(3), 4474-4491. Advance online publication. https://doi.org/10.1109/tte.2023.3244580

Vancouver

Li X, Cao Y, Wan S, Liu S, Lin H, Zhu Y. A Coordinated Battery Swapping Service Management Scheme Based on Battery Heterogeneity. IEEE Transactions on Transportation Electrification. 2023 Feb 13;9(3):4474-4491. Epub 2023 Feb 13. doi: 10.1109/tte.2023.3244580

Author

Li, Xinyu ; Cao, Yue ; Wan, Shaohua et al. / A Coordinated Battery Swapping Service Management Scheme Based on Battery Heterogeneity. In: IEEE Transactions on Transportation Electrification. 2023 ; Vol. 9, No. 3. pp. 4474-4491.

Bibtex

@article{aeabcc9737044228a267f44e76f42688,
title = "A Coordinated Battery Swapping Service Management Scheme Based on Battery Heterogeneity",
abstract = "The service management based on battery heterogeneity has become an increasingly important research problem in battery swapping technology. In this paper, with the method of bipartite matching, we first theoretically analyse the offline optimization problem of battery swapping service under battery heterogeneity. Nevertheless, the information of global view used in offline optimization solution cannot be known in advance during real-time operation. To address the disadvantage, an online framework comprising several sub-procedures is proposed for heterogeneous battery implementation. Firstly, by incorporating battery swapping station (BSS) local status such as charging and waiting queue of heterogeneous batteries, a charging slot allocation mechanism is designed. Utilizing the proposed allocation method, the charging priority is determined by the proportion of heterogeneous batteries demand, so as to guarantee charging fairness. Secondly, with the help of reservation information, the proposed allocation method can further be improved by predicting the future arrival distribution of heterogeneous types of electric vehicles. Thirdly, according to the service demand prediction based on long short-term memory neural network, joint optimization of BSS-selection and charging cost can be achieved by charging power adjustment. Simulation results indicate the desirable performance of proposed scheme in balancing the demands of multi-party participators.",
keywords = "Electrical and Electronic Engineering, Energy Engineering and Power Technology, Transportation, Automotive Engineering",
author = "Xinyu Li and Yue Cao and Shaohua Wan and Shuohan Liu and Hai Lin and Yongdong Zhu",
year = "2023",
month = feb,
day = "13",
doi = "10.1109/tte.2023.3244580",
language = "English",
volume = "9",
pages = "4474--4491",
journal = "IEEE Transactions on Transportation Electrification",
number = "3",

}

RIS

TY - JOUR

T1 - A Coordinated Battery Swapping Service Management Scheme Based on Battery Heterogeneity

AU - Li, Xinyu

AU - Cao, Yue

AU - Wan, Shaohua

AU - Liu, Shuohan

AU - Lin, Hai

AU - Zhu, Yongdong

PY - 2023/2/13

Y1 - 2023/2/13

N2 - The service management based on battery heterogeneity has become an increasingly important research problem in battery swapping technology. In this paper, with the method of bipartite matching, we first theoretically analyse the offline optimization problem of battery swapping service under battery heterogeneity. Nevertheless, the information of global view used in offline optimization solution cannot be known in advance during real-time operation. To address the disadvantage, an online framework comprising several sub-procedures is proposed for heterogeneous battery implementation. Firstly, by incorporating battery swapping station (BSS) local status such as charging and waiting queue of heterogeneous batteries, a charging slot allocation mechanism is designed. Utilizing the proposed allocation method, the charging priority is determined by the proportion of heterogeneous batteries demand, so as to guarantee charging fairness. Secondly, with the help of reservation information, the proposed allocation method can further be improved by predicting the future arrival distribution of heterogeneous types of electric vehicles. Thirdly, according to the service demand prediction based on long short-term memory neural network, joint optimization of BSS-selection and charging cost can be achieved by charging power adjustment. Simulation results indicate the desirable performance of proposed scheme in balancing the demands of multi-party participators.

AB - The service management based on battery heterogeneity has become an increasingly important research problem in battery swapping technology. In this paper, with the method of bipartite matching, we first theoretically analyse the offline optimization problem of battery swapping service under battery heterogeneity. Nevertheless, the information of global view used in offline optimization solution cannot be known in advance during real-time operation. To address the disadvantage, an online framework comprising several sub-procedures is proposed for heterogeneous battery implementation. Firstly, by incorporating battery swapping station (BSS) local status such as charging and waiting queue of heterogeneous batteries, a charging slot allocation mechanism is designed. Utilizing the proposed allocation method, the charging priority is determined by the proportion of heterogeneous batteries demand, so as to guarantee charging fairness. Secondly, with the help of reservation information, the proposed allocation method can further be improved by predicting the future arrival distribution of heterogeneous types of electric vehicles. Thirdly, according to the service demand prediction based on long short-term memory neural network, joint optimization of BSS-selection and charging cost can be achieved by charging power adjustment. Simulation results indicate the desirable performance of proposed scheme in balancing the demands of multi-party participators.

KW - Electrical and Electronic Engineering

KW - Energy Engineering and Power Technology

KW - Transportation

KW - Automotive Engineering

U2 - 10.1109/tte.2023.3244580

DO - 10.1109/tte.2023.3244580

M3 - Journal article

VL - 9

SP - 4474

EP - 4491

JO - IEEE Transactions on Transportation Electrification

JF - IEEE Transactions on Transportation Electrification

IS - 3

ER -