Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles

Huilong Yu; Dongpu Cao

doi:10.1109/IVS.2018.8500629

Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles

Huilong Yu
, Dongpu Cao

Vehicle Intelligence Pioneers Inc.
University of Waterloo

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

11 引用（Scopus）

摘要

Hybrid energy storage system (HESS) has been recognized as one of the most promising solutions to overcome the drawbacks of the expensive and short life lithium-ion battery with low power density, by introducing a proper number of supercapcitors. However, the hybridization introduces complicated sizing and energy management problems. This papers aims to investigate the sizing and real-time energy management of a devised HESS for electric vehicles with an electric race car as a case study. In particular, a proposed multi-objective Bi-level optimal sizing and control framework is implemented to find the optimal parameters of the energy management algorithm, the optimal number of the lithiumion battery cells and the supercapacitor banks. The simulation results have validated the effectiveness of the investigated methodology in minimizing the total mass of the HESS and maximizing the cycle life of the lithium-ion battery.

源语言	英语
主期刊名	2018 IEEE Intelligent Vehicles Symposium, IV 2018
出版商	Institute of Electrical and Electronics Engineers Inc.
页	191-196
页数	6
ISBN（电子版）	9781538644522
DOI	https://doi.org/10.1109/IVS.2018.8500629
出版状态	已出版 - 18 10月 2018
已对外发布	是
活动	2018 IEEE Intelligent Vehicles Symposium, IV 2018 - Changshu, Suzhou, 中国期限: 26 9月 2018 → 30 9月 2018

丛书

姓名	IEEE Intelligent Vehicles Symposium, Proceedings
卷	2018-June
ISSN（印刷版）	1931-0587
ISSN（电子版）	2642-7214

会议

会议	2018 IEEE Intelligent Vehicles Symposium, IV 2018
国家/地区	中国
市	Changshu, Suzhou
时期	26/09/18 → 30/09/18

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/IVS.2018.8500629

其它文件与链接

链接到 Scopus 的出版物

引用此

Yu, H., & Cao, D. (2018). Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles. 在 2018 IEEE Intelligent Vehicles Symposium, IV 2018 (页码 191-196). 期刊论文 8500629 (IEEE Intelligent Vehicles Symposium, Proceedings; 卷 2018-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IVS.2018.8500629

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title = "Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles",

abstract = "Hybrid energy storage system (HESS) has been recognized as one of the most promising solutions to overcome the drawbacks of the expensive and short life lithium-ion battery with low power density, by introducing a proper number of supercapcitors. However, the hybridization introduces complicated sizing and energy management problems. This papers aims to investigate the sizing and real-time energy management of a devised HESS for electric vehicles with an electric race car as a case study. In particular, a proposed multi-objective Bi-level optimal sizing and control framework is implemented to find the optimal parameters of the energy management algorithm, the optimal number of the lithiumion battery cells and the supercapacitor banks. The simulation results have validated the effectiveness of the investigated methodology in minimizing the total mass of the HESS and maximizing the cycle life of the lithium-ion battery.",

author = "Huilong Yu and Dongpu Cao",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Intelligent Vehicles Symposium, IV 2018 ; Conference date: 26-09-2018 Through 30-09-2018",

year = "2018",

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doi = "10.1109/IVS.2018.8500629",

language = "English",

series = "IEEE Intelligent Vehicles Symposium, Proceedings",

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Yu, H & Cao, D 2018, Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles. 在 2018 IEEE Intelligent Vehicles Symposium, IV 2018., 8500629, IEEE Intelligent Vehicles Symposium, Proceedings, 卷 2018-June, Institute of Electrical and Electronics Engineers Inc., 页码 191-196, 2018 IEEE Intelligent Vehicles Symposium, IV 2018, Changshu, Suzhou, 中国, 26/09/18. https://doi.org/10.1109/IVS.2018.8500629

Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles. / Yu, Huilong; Cao, Dongpu.
2018 IEEE Intelligent Vehicles Symposium, IV 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 页码 191-196 8500629 (IEEE Intelligent Vehicles Symposium, Proceedings; 卷 2018-June).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles

AU - Yu, Huilong

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N2 - Hybrid energy storage system (HESS) has been recognized as one of the most promising solutions to overcome the drawbacks of the expensive and short life lithium-ion battery with low power density, by introducing a proper number of supercapcitors. However, the hybridization introduces complicated sizing and energy management problems. This papers aims to investigate the sizing and real-time energy management of a devised HESS for electric vehicles with an electric race car as a case study. In particular, a proposed multi-objective Bi-level optimal sizing and control framework is implemented to find the optimal parameters of the energy management algorithm, the optimal number of the lithiumion battery cells and the supercapacitor banks. The simulation results have validated the effectiveness of the investigated methodology in minimizing the total mass of the HESS and maximizing the cycle life of the lithium-ion battery.

AB - Hybrid energy storage system (HESS) has been recognized as one of the most promising solutions to overcome the drawbacks of the expensive and short life lithium-ion battery with low power density, by introducing a proper number of supercapcitors. However, the hybridization introduces complicated sizing and energy management problems. This papers aims to investigate the sizing and real-time energy management of a devised HESS for electric vehicles with an electric race car as a case study. In particular, a proposed multi-objective Bi-level optimal sizing and control framework is implemented to find the optimal parameters of the energy management algorithm, the optimal number of the lithiumion battery cells and the supercapacitor banks. The simulation results have validated the effectiveness of the investigated methodology in minimizing the total mass of the HESS and maximizing the cycle life of the lithium-ion battery.

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M3 - Conference contribution

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T3 - IEEE Intelligent Vehicles Symposium, Proceedings

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BT - 2018 IEEE Intelligent Vehicles Symposium, IV 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE Intelligent Vehicles Symposium, IV 2018

Y2 - 26 September 2018 through 30 September 2018

ER -

Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles

摘要

丛书

会议

联合国可持续发展目标

访问文件

其它文件与链接

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引用此