High accurate lithium-ion battery SOC estimation with data-driven battery model

Xiao Cai; Guangzhao Luo

High accurate lithium-ion battery SOC estimation with data-driven battery model

School of Automation

Xi′an ACT Acoustic Technology Co.,Ltd.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Original language	English
Title of host publication	Global Battery Raw Materials Symposium 2018, Held at AABC Europe 2018
Publisher	Cambridge EnerTech, Cambridge Innovation Institute
Pages	362-363
Number of pages	2
ISBN (Electronic)	9781510859067
State	Published - 2018
Event	Global Battery Raw Materials Symposium 2018 - Mainz, Germany Duration: 29 Jan 2018 → 1 Feb 2018

Publication series

Name	Global Battery Raw Materials Symposium 2018, Held at AABC Europe 2018

Conference

Conference	Global Battery Raw Materials Symposium 2018
Country/Territory	Germany
City	Mainz
Period	29/01/18 → 1/02/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

@inproceedings{83bb665a2a374de5858d9039642b3608,

title = "High accurate lithium-ion battery SOC estimation with data-driven battery model",

author = "Xiao Cai and Guangzhao Luo",

year = "2018",

language = "英语",

series = "Global Battery Raw Materials Symposium 2018, Held at AABC Europe 2018",

publisher = "Cambridge EnerTech, Cambridge Innovation Institute",

pages = "362--363",

booktitle = "Global Battery Raw Materials Symposium 2018, Held at AABC Europe 2018",

note = "Global Battery Raw Materials Symposium 2018 ; Conference date: 29-01-2018 Through 01-02-2018",

}

Cai, X & Luo, G 2018, High accurate lithium-ion battery SOC estimation with data-driven battery model. in Global Battery Raw Materials Symposium 2018, Held at AABC Europe 2018. Global Battery Raw Materials Symposium 2018, Held at AABC Europe 2018, Cambridge EnerTech, Cambridge Innovation Institute, pp. 362-363, Global Battery Raw Materials Symposium 2018, Mainz, Germany, 29/01/18.

High accurate lithium-ion battery SOC estimation with data-driven battery model. / Cai, Xiao; Luo, Guangzhao.
Global Battery Raw Materials Symposium 2018, Held at AABC Europe 2018. Cambridge EnerTech, Cambridge Innovation Institute, 2018. p. 362-363 (Global Battery Raw Materials Symposium 2018, Held at AABC Europe 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - High accurate lithium-ion battery SOC estimation with data-driven battery model

AU - Cai, Xiao

AU - Luo, Guangzhao

PY - 2018

Y1 - 2018

UR - http://www.scopus.com/inward/record.url?scp=85048630836&partnerID=8YFLogxK

M3 - 会议稿件

AN - SCOPUS:85048630836

T3 - Global Battery Raw Materials Symposium 2018, Held at AABC Europe 2018

SP - 362

EP - 363

BT - Global Battery Raw Materials Symposium 2018, Held at AABC Europe 2018

PB - Cambridge EnerTech, Cambridge Innovation Institute

T2 - Global Battery Raw Materials Symposium 2018

Y2 - 29 January 2018 through 1 February 2018

ER -

High accurate lithium-ion battery SOC estimation with data-driven battery model

Publication series

Conference

UN SDGs

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Cite this