A data-driven bias correction method based lithium-ion battery modeling approach for electric vehicles application

Xianzhi Gong; Rui Xiong; Chunting Chris Mi

doi:10.1109/itec.2014.6861807

A data-driven bias correction method based lithium-ion battery modeling approach for electric vehicles application

Xianzhi Gong
, Rui Xiong
, Chunting Chris Mi^*

^*此作品的通讯作者

机械与车辆学院

University of Michigan, Dearborn

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

8 引用（Scopus）

摘要

Due to the inconsistency and varied characteristics of lithium-ion battery cells, the battery pack modeling remains a challenging problem. To model the operation behaviors of each cell in the battery pack, considerable work effort and computation time is needed. This paper proposes a data-driven bias correction based lithium-ion battery modeling method, which can significantly reduce the computation work and remain good model accuracy.

源语言	英语
主期刊名	2014 IEEE Transportation Electrification Conference and Expo
主期刊副标题	Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014
出版商	Institute of Electrical and Electronics Engineers Inc.
ISBN（电子版）	9781479922628
DOI	https://doi.org/10.1109/itec.2014.6861807
出版状态	已出版 - 21 7月 2014
活动	2014 IEEE Transportation Electrification Conference and Expo, ITEC 2014 - Dearborn, 美国期限: 15 6月 2014 → 18 6月 2014

丛书

姓名	2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014

会议

会议	2014 IEEE Transportation Electrification Conference and Expo, ITEC 2014
国家/地区	美国
市	Dearborn
时期	15/06/14 → 18/06/14

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/itec.2014.6861807

其它文件与链接

链接到 Scopus 的出版物

引用此

Gong, X., Xiong, R., & Mi, C. C. (2014). A data-driven bias correction method based lithium-ion battery modeling approach for electric vehicles application. 在 2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014 期刊论文 6861807 (2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/itec.2014.6861807

Gong, Xianzhi ; Xiong, Rui ; Mi, Chunting Chris. / A data-driven bias correction method based lithium-ion battery modeling approach for electric vehicles application. 2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. (2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014).

@inproceedings{b494acd9dad24df6920d367c0faa8cbe,

title = "A data-driven bias correction method based lithium-ion battery modeling approach for electric vehicles application",

abstract = "Due to the inconsistency and varied characteristics of lithium-ion battery cells, the battery pack modeling remains a challenging problem. To model the operation behaviors of each cell in the battery pack, considerable work effort and computation time is needed. This paper proposes a data-driven bias correction based lithium-ion battery modeling method, which can significantly reduce the computation work and remain good model accuracy.",

author = "Xianzhi Gong and Rui Xiong and Mi, \{Chunting Chris\}",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE Transportation Electrification Conference and Expo, ITEC 2014 ; Conference date: 15-06-2014 Through 18-06-2014",

year = "2014",

month = jul,

day = "21",

doi = "10.1109/itec.2014.6861807",

language = "English",

series = "2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014",

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

booktitle = "2014 IEEE Transportation Electrification Conference and Expo",

address = "United States",

}

Gong, X, Xiong, R & Mi, CC 2014, A data-driven bias correction method based lithium-ion battery modeling approach for electric vehicles application. 在 2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014., 6861807, 2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014, Institute of Electrical and Electronics Engineers Inc., 2014 IEEE Transportation Electrification Conference and Expo, ITEC 2014, Dearborn, 美国, 15/06/14. https://doi.org/10.1109/itec.2014.6861807

A data-driven bias correction method based lithium-ion battery modeling approach for electric vehicles application. / Gong, Xianzhi; Xiong, Rui; Mi, Chunting Chris.
2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. 6861807 (2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - A data-driven bias correction method based lithium-ion battery modeling approach for electric vehicles application

AU - Gong, Xianzhi

AU - Xiong, Rui

AU - Mi, Chunting Chris

PY - 2014/7/21

Y1 - 2014/7/21

N2 - Due to the inconsistency and varied characteristics of lithium-ion battery cells, the battery pack modeling remains a challenging problem. To model the operation behaviors of each cell in the battery pack, considerable work effort and computation time is needed. This paper proposes a data-driven bias correction based lithium-ion battery modeling method, which can significantly reduce the computation work and remain good model accuracy.

AB - Due to the inconsistency and varied characteristics of lithium-ion battery cells, the battery pack modeling remains a challenging problem. To model the operation behaviors of each cell in the battery pack, considerable work effort and computation time is needed. This paper proposes a data-driven bias correction based lithium-ion battery modeling method, which can significantly reduce the computation work and remain good model accuracy.

UR - https://www.scopus.com/pages/publications/84912103095

U2 - 10.1109/itec.2014.6861807

DO - 10.1109/itec.2014.6861807

M3 - Conference contribution

AN - SCOPUS:84912103095

T3 - 2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014

BT - 2014 IEEE Transportation Electrification Conference and Expo

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2014 IEEE Transportation Electrification Conference and Expo, ITEC 2014

Y2 - 15 June 2014 through 18 June 2014

ER -

Gong X, Xiong R, Mi CC. A data-driven bias correction method based lithium-ion battery modeling approach for electric vehicles application. 在 2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. 6861807. (2014 IEEE Transportation Electrification Conference and Expo: Components, Systems, and Power Electronics - From Technology to Business and Public Policy, ITEC 2014). doi: 10.1109/itec.2014.6861807

A data-driven bias correction method based lithium-ion battery modeling approach for electric vehicles application

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

学术指纹

引用此