High efficiency electric vehicle charging strategy based on model predictive control

Shichun Yang; Xinan Zhou; Yang Hua; Rong He; Xinhua Liu; Sida Zhou

doi:10.1109/AUTEEE48671.2019.9033164

High efficiency electric vehicle charging strategy based on model predictive control

Shichun Yang
, Xinan Zhou
, Yang Hua
, Rong He
, Xinhua Liu
, Sida Zhou

交通科学与工程学院

Beihang University
Imperial College London

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

The accuracy of lithium-ion battery charging control has a profound effect on the cycle life and safety of battery system in electric vehicles. Therefore, we propose a highly efficient charging method based on model predictive control. A high-precision SOC estimation approach can be carried out by unscented Kalman filter based on Thevenin model, and parameters are identified by simulated annealing algorithm. Further, the model predict control is presented and the implementation is realized. Finally, precision of SOC estimation is validated by experiment. Simulation results show that compared with the CCCV method, the proposed battery charging strategy has advantages of both high accuracy and high efficiency, hence delivering its practicability to be extended to battery systems applying complex operating conditions.

源语言	英语
主期刊名	Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019
出版商	Institute of Electrical and Electronics Engineers Inc.
页	54-59
页数	6
ISBN（电子版）	9781728150291
DOI	https://doi.org/10.1109/AUTEEE48671.2019.9033164
出版状态	已出版 - 11月 2019
活动	2nd IEEE International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019 - Shenyang, 中国期限: 22 11月 2019 → 24 11月 2019

出版系列

姓名	Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019

会议

会议	2nd IEEE International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019
国家/地区	中国
市	Shenyang
时期	22/11/19 → 24/11/19

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 7 经济适用的清洁能源

访问文件

10.1109/AUTEEE48671.2019.9033164

其它文件与链接

链接到 Scopus 的出版物

引用此

Yang, S., Zhou, X., Hua, Y., He, R., Liu, X., & Zhou, S. (2019). High efficiency electric vehicle charging strategy based on model predictive control. 在 Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019 (页码 54-59). 文章 9033164 (Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AUTEEE48671.2019.9033164

Yang, Shichun ; Zhou, Xinan ; Hua, Yang 等. / High efficiency electric vehicle charging strategy based on model predictive control. Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 页码 54-59 (Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019).

@inproceedings{33797f5e65a64e4eb43172f2aee854bf,

title = "High efficiency electric vehicle charging strategy based on model predictive control",

abstract = "The accuracy of lithium-ion battery charging control has a profound effect on the cycle life and safety of battery system in electric vehicles. Therefore, we propose a highly efficient charging method based on model predictive control. A high-precision SOC estimation approach can be carried out by unscented Kalman filter based on Thevenin model, and parameters are identified by simulated annealing algorithm. Further, the model predict control is presented and the implementation is realized. Finally, precision of SOC estimation is validated by experiment. Simulation results show that compared with the CCCV method, the proposed battery charging strategy has advantages of both high accuracy and high efficiency, hence delivering its practicability to be extended to battery systems applying complex operating conditions.",

keywords = "Battery charging strategy, Lithium-ion battery, Model predict control, Unscented Kalman filter",

author = "Shichun Yang and Xinan Zhou and Yang Hua and Rong He and Xinhua Liu and Sida Zhou",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2nd IEEE International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019 ; Conference date: 22-11-2019 Through 24-11-2019",

year = "2019",

month = nov,

doi = "10.1109/AUTEEE48671.2019.9033164",

language = "英语",

series = "Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019",

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

pages = "54--59",

booktitle = "Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019",

address = "美国",

}

Yang, S, Zhou, X, Hua, Y, He, R, Liu, X & Zhou, S 2019, High efficiency electric vehicle charging strategy based on model predictive control. 在 Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019., 9033164, Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019, Institute of Electrical and Electronics Engineers Inc., 页码 54-59, 2nd IEEE International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019, Shenyang, 中国, 22/11/19. https://doi.org/10.1109/AUTEEE48671.2019.9033164

High efficiency electric vehicle charging strategy based on model predictive control. / Yang, Shichun; Zhou, Xinan; Hua, Yang 等.
Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 页码 54-59 9033164 (Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - High efficiency electric vehicle charging strategy based on model predictive control

AU - Yang, Shichun

AU - Zhou, Xinan

AU - Hua, Yang

AU - He, Rong

AU - Liu, Xinhua

AU - Zhou, Sida

PY - 2019/11

Y1 - 2019/11

N2 - The accuracy of lithium-ion battery charging control has a profound effect on the cycle life and safety of battery system in electric vehicles. Therefore, we propose a highly efficient charging method based on model predictive control. A high-precision SOC estimation approach can be carried out by unscented Kalman filter based on Thevenin model, and parameters are identified by simulated annealing algorithm. Further, the model predict control is presented and the implementation is realized. Finally, precision of SOC estimation is validated by experiment. Simulation results show that compared with the CCCV method, the proposed battery charging strategy has advantages of both high accuracy and high efficiency, hence delivering its practicability to be extended to battery systems applying complex operating conditions.

AB - The accuracy of lithium-ion battery charging control has a profound effect on the cycle life and safety of battery system in electric vehicles. Therefore, we propose a highly efficient charging method based on model predictive control. A high-precision SOC estimation approach can be carried out by unscented Kalman filter based on Thevenin model, and parameters are identified by simulated annealing algorithm. Further, the model predict control is presented and the implementation is realized. Finally, precision of SOC estimation is validated by experiment. Simulation results show that compared with the CCCV method, the proposed battery charging strategy has advantages of both high accuracy and high efficiency, hence delivering its practicability to be extended to battery systems applying complex operating conditions.

KW - Battery charging strategy

KW - Lithium-ion battery

KW - Model predict control

KW - Unscented Kalman filter

UR - https://www.scopus.com/pages/publications/85083262669

U2 - 10.1109/AUTEEE48671.2019.9033164

DO - 10.1109/AUTEEE48671.2019.9033164

M3 - 会议稿件

AN - SCOPUS:85083262669

T3 - Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019

SP - 54

EP - 59

BT - Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd IEEE International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019

Y2 - 22 November 2019 through 24 November 2019

ER -

Yang S, Zhou X, Hua Y, He R, Liu X, Zhou S. High efficiency electric vehicle charging strategy based on model predictive control. 在 Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 页码 54-59. 9033164. (Proceedings of 2019 IEEE 2nd International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2019). doi: 10.1109/AUTEEE48671.2019.9033164

High efficiency electric vehicle charging strategy based on model predictive control

摘要

出版系列

会议

联合国可持续发展目标

访问文件

其它文件与链接

指纹

引用此