RUL estimation of lithium-ion power battery based on DEKF algorithm

Anyuan Wang; Haitao Chen; Peng Jin; Jun Huang; Dong Feng; Minxin Zheng

doi:10.1109/ICIEA.2019.8833805

RUL estimation of lithium-ion power battery based on DEKF algorithm

Anyuan Wang
, Haitao Chen
, Peng Jin
, Jun Huang
, Dong Feng
, Minxin Zheng

School of Mechanical Engineering and Automation

Beihang University
Shanghai Institute of Space Power Sources

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

9 Scopus citations

Abstract

Lithium-ion power batteries are the energy source for many complex electronic systems, and their Remaining Useful Life (RUL) is critical to the safety and reliability of power systems. The high-precision estimation of lithium-ion battery life has become one of the current research hotspots, and has attracted more and more scholars' attention. In order to realize the residual cycle life estimation of lithium ion power battery, an equivalent circuit model is established for lithium ion power battery. Based on the HPPC pulse experimental data, the second-order Thevenin equivalent circuit model is selected, combined with the equivalent circuit model and battery capacity model. The state equation and measurement equation of the double extended Kalman filter algorithm and the specific iterative recursive calculation process. The accuracy and adaptability of the algorithm are verified by the actual discharge conditions. Finally, based on the life data of this experimental object, the battery RUL estimation within a reasonable error range was made. It is of great significance to improve the safety, reliability and economic benefits of the system.

Original language	English
Title of host publication	Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1851-1856
Number of pages	6
ISBN (Electronic)	9781538694909
DOIs	https://doi.org/10.1109/ICIEA.2019.8833805
State	Published - Jun 2019
Event	14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019 - Xi'an, China Duration: 19 Jun 2019 → 21 Jun 2019

Publication series

Name	Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019

Conference

Conference	14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019
Country/Territory	China
City	Xi'an
Period	19/06/19 → 21/06/19

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Battery model
Dual extended Kalman filter
Health status
Lithium-ion battery
Residual cycle life

Access to Document

10.1109/ICIEA.2019.8833805

Cite this

Wang, A., Chen, H., Jin, P., Huang, J., Feng, D., & Zheng, M. (2019). RUL estimation of lithium-ion power battery based on DEKF algorithm. In Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019 (pp. 1851-1856). Article 8833805 (Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIEA.2019.8833805

Wang, Anyuan ; Chen, Haitao ; Jin, Peng et al. / RUL estimation of lithium-ion power battery based on DEKF algorithm. Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1851-1856 (Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019).

@inproceedings{206d66c9769d43a1a6a3d83d7369f11e,

title = "RUL estimation of lithium-ion power battery based on DEKF algorithm",

abstract = "Lithium-ion power batteries are the energy source for many complex electronic systems, and their Remaining Useful Life (RUL) is critical to the safety and reliability of power systems. The high-precision estimation of lithium-ion battery life has become one of the current research hotspots, and has attracted more and more scholars' attention. In order to realize the residual cycle life estimation of lithium ion power battery, an equivalent circuit model is established for lithium ion power battery. Based on the HPPC pulse experimental data, the second-order Thevenin equivalent circuit model is selected, combined with the equivalent circuit model and battery capacity model. The state equation and measurement equation of the double extended Kalman filter algorithm and the specific iterative recursive calculation process. The accuracy and adaptability of the algorithm are verified by the actual discharge conditions. Finally, based on the life data of this experimental object, the battery RUL estimation within a reasonable error range was made. It is of great significance to improve the safety, reliability and economic benefits of the system.",

keywords = "Battery model, Dual extended Kalman filter, Health status, Lithium-ion battery, Residual cycle life",

author = "Anyuan Wang and Haitao Chen and Peng Jin and Jun Huang and Dong Feng and Minxin Zheng",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019 ; Conference date: 19-06-2019 Through 21-06-2019",

year = "2019",

month = jun,

doi = "10.1109/ICIEA.2019.8833805",

language = "英语",

series = "Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019",

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

pages = "1851--1856",

booktitle = "Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019",

address = "美国",

}

Wang, A, Chen, H, Jin, P, Huang, J, Feng, D & Zheng, M 2019, RUL estimation of lithium-ion power battery based on DEKF algorithm. in Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019., 8833805, Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1851-1856, 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019, Xi'an, China, 19/06/19. https://doi.org/10.1109/ICIEA.2019.8833805

RUL estimation of lithium-ion power battery based on DEKF algorithm. / Wang, Anyuan; Chen, Haitao; Jin, Peng et al.
Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1851-1856 8833805 (Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019).

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

TY - GEN

T1 - RUL estimation of lithium-ion power battery based on DEKF algorithm

AU - Wang, Anyuan

AU - Chen, Haitao

AU - Jin, Peng

AU - Huang, Jun

AU - Feng, Dong

AU - Zheng, Minxin

PY - 2019/6

Y1 - 2019/6

N2 - Lithium-ion power batteries are the energy source for many complex electronic systems, and their Remaining Useful Life (RUL) is critical to the safety and reliability of power systems. The high-precision estimation of lithium-ion battery life has become one of the current research hotspots, and has attracted more and more scholars' attention. In order to realize the residual cycle life estimation of lithium ion power battery, an equivalent circuit model is established for lithium ion power battery. Based on the HPPC pulse experimental data, the second-order Thevenin equivalent circuit model is selected, combined with the equivalent circuit model and battery capacity model. The state equation and measurement equation of the double extended Kalman filter algorithm and the specific iterative recursive calculation process. The accuracy and adaptability of the algorithm are verified by the actual discharge conditions. Finally, based on the life data of this experimental object, the battery RUL estimation within a reasonable error range was made. It is of great significance to improve the safety, reliability and economic benefits of the system.

AB - Lithium-ion power batteries are the energy source for many complex electronic systems, and their Remaining Useful Life (RUL) is critical to the safety and reliability of power systems. The high-precision estimation of lithium-ion battery life has become one of the current research hotspots, and has attracted more and more scholars' attention. In order to realize the residual cycle life estimation of lithium ion power battery, an equivalent circuit model is established for lithium ion power battery. Based on the HPPC pulse experimental data, the second-order Thevenin equivalent circuit model is selected, combined with the equivalent circuit model and battery capacity model. The state equation and measurement equation of the double extended Kalman filter algorithm and the specific iterative recursive calculation process. The accuracy and adaptability of the algorithm are verified by the actual discharge conditions. Finally, based on the life data of this experimental object, the battery RUL estimation within a reasonable error range was made. It is of great significance to improve the safety, reliability and economic benefits of the system.

KW - Battery model

KW - Dual extended Kalman filter

KW - Health status

KW - Lithium-ion battery

KW - Residual cycle life

UR - https://www.scopus.com/pages/publications/85073065236

U2 - 10.1109/ICIEA.2019.8833805

DO - 10.1109/ICIEA.2019.8833805

M3 - 会议稿件

AN - SCOPUS:85073065236

T3 - Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019

SP - 1851

EP - 1856

BT - Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019

Y2 - 19 June 2019 through 21 June 2019

ER -

Wang A, Chen H, Jin P, Huang J, Feng D, Zheng M. RUL estimation of lithium-ion power battery based on DEKF algorithm. In Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1851-1856. 8833805. (Proceedings of the 14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019). doi: 10.1109/ICIEA.2019.8833805

RUL estimation of lithium-ion power battery based on DEKF algorithm

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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