Moving Horizon Estimation based Unknown Input Observer for Lithium-Ion Batteries

Jian Hu; Zhongbao Wei; Hongwen He

doi:10.1109/ECCE-Asia49820.2021.9479173

Moving Horizon Estimation based Unknown Input Observer for Lithium-Ion Batteries

School of Mechanical Engineering

Beijing Institute of Technology

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

3 Citations (Scopus)

Abstract

Battery state estimation is the key function of the battery management system which relies heavily on accurate current measurements. However, for the newly designed intelligent batteries with a lot of sensors and controllers integrated, the current sensors are expensive and easily disturbed. To this end, this paper proposed a moving horizon estimation (MHE)-based unknown input state observer (UIO) for the lithium-ion batteries to estimate the states of the battery. First, a first order RC battery model is built in Simulink, based on which the state-space function is derived. Then, the parameters of the model are identified offline and the MHE-based UIO is designed. The proposed method is validated for the superiority in SOC estimation without knowledge of the load current.

Original language	English
Title of host publication	Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	959-962
Number of pages	4
ISBN (Electronic)	9781728163444
DOIs	https://doi.org/10.1109/ECCE-Asia49820.2021.9479173
Publication status	Published - 24 May 2021
Event	12th IEEE Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021 - Virtual, Singapore, Singapore Duration: 24 May 2021 → 27 May 2021

Publication series

Name	Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021

Conference

Conference	12th IEEE Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
Country/Territory	Singapore
City	Virtual, Singapore
Period	24/05/21 → 27/05/21

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

lithium-ion battery
moving horizon estimation
state of charge
unknown input observer

Access to Document

10.1109/ECCE-Asia49820.2021.9479173

Cite this

Hu, J., Wei, Z., & He, H. (2021). Moving Horizon Estimation based Unknown Input Observer for Lithium-Ion Batteries. In Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021 (pp. 959-962). Article 9479173 (Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECCE-Asia49820.2021.9479173

Hu, Jian ; Wei, Zhongbao ; He, Hongwen. / Moving Horizon Estimation based Unknown Input Observer for Lithium-Ion Batteries. Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 959-962 (Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021).

@inproceedings{920f254500ed456f8388d4d05988e5d7,

title = "Moving Horizon Estimation based Unknown Input Observer for Lithium-Ion Batteries",

abstract = "Battery state estimation is the key function of the battery management system which relies heavily on accurate current measurements. However, for the newly designed intelligent batteries with a lot of sensors and controllers integrated, the current sensors are expensive and easily disturbed. To this end, this paper proposed a moving horizon estimation (MHE)-based unknown input state observer (UIO) for the lithium-ion batteries to estimate the states of the battery. First, a first order RC battery model is built in Simulink, based on which the state-space function is derived. Then, the parameters of the model are identified offline and the MHE-based UIO is designed. The proposed method is validated for the superiority in SOC estimation without knowledge of the load current.",

keywords = "lithium-ion battery, moving horizon estimation, state of charge, unknown input observer",

author = "Jian Hu and Zhongbao Wei and Hongwen He",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 12th IEEE Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021 ; Conference date: 24-05-2021 Through 27-05-2021",

year = "2021",

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doi = "10.1109/ECCE-Asia49820.2021.9479173",

language = "English",

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Hu, J, Wei, Z & He, H 2021, Moving Horizon Estimation based Unknown Input Observer for Lithium-Ion Batteries. in Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021., 9479173, Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021, Institute of Electrical and Electronics Engineers Inc., pp. 959-962, 12th IEEE Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021, Virtual, Singapore, Singapore, 24/05/21. https://doi.org/10.1109/ECCE-Asia49820.2021.9479173

Moving Horizon Estimation based Unknown Input Observer for Lithium-Ion Batteries. / Hu, Jian; Wei, Zhongbao ; He, Hongwen.
Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 959-962 9479173 (Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021).

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

TY - GEN

T1 - Moving Horizon Estimation based Unknown Input Observer for Lithium-Ion Batteries

AU - Hu, Jian

AU - Wei, Zhongbao

AU - He, Hongwen

PY - 2021/5/24

Y1 - 2021/5/24

N2 - Battery state estimation is the key function of the battery management system which relies heavily on accurate current measurements. However, for the newly designed intelligent batteries with a lot of sensors and controllers integrated, the current sensors are expensive and easily disturbed. To this end, this paper proposed a moving horizon estimation (MHE)-based unknown input state observer (UIO) for the lithium-ion batteries to estimate the states of the battery. First, a first order RC battery model is built in Simulink, based on which the state-space function is derived. Then, the parameters of the model are identified offline and the MHE-based UIO is designed. The proposed method is validated for the superiority in SOC estimation without knowledge of the load current.

AB - Battery state estimation is the key function of the battery management system which relies heavily on accurate current measurements. However, for the newly designed intelligent batteries with a lot of sensors and controllers integrated, the current sensors are expensive and easily disturbed. To this end, this paper proposed a moving horizon estimation (MHE)-based unknown input state observer (UIO) for the lithium-ion batteries to estimate the states of the battery. First, a first order RC battery model is built in Simulink, based on which the state-space function is derived. Then, the parameters of the model are identified offline and the MHE-based UIO is designed. The proposed method is validated for the superiority in SOC estimation without knowledge of the load current.

KW - lithium-ion battery

KW - moving horizon estimation

KW - state of charge

KW - unknown input observer

UR - https://www.scopus.com/pages/publications/85114208886

U2 - 10.1109/ECCE-Asia49820.2021.9479173

DO - 10.1109/ECCE-Asia49820.2021.9479173

M3 - Conference contribution

AN - SCOPUS:85114208886

T3 - Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021

SP - 959

EP - 962

BT - Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 12th IEEE Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021

Y2 - 24 May 2021 through 27 May 2021

ER -

Hu J, Wei Z , He H. Moving Horizon Estimation based Unknown Input Observer for Lithium-Ion Batteries. In Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 959-962. 9479173. (Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021). doi: 10.1109/ECCE-Asia49820.2021.9479173

Moving Horizon Estimation based Unknown Input Observer for Lithium-Ion Batteries

Abstract

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UN SDGs

Keywords

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