SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF

Honggang Du; Guangchen Liu; Jianwei Zhang; Guizhen Tian; Shengtie Wang

doi:10.1109/REPE52765.2021.9617029

SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF

Honggang Du
, Guangchen Liu
, Jianwei Zhang
, Guizhen Tian
, Shengtie Wang

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

4 Citations (Scopus)

Abstract

Accurate estimation of the state of charge (SOC) of Lithium-ion batteries is the critical technology for developing Lithium-ion batteries. Aiming at the problem that the noise covariance of the UKF is fixed, an adaptive UKF algorithm is proposed in this paper. The adaptive UKF algorithm can estimate and correct the noise characteristics of the system in real-Time, and suppress the possible filter divergence and improve the estimation accuracy of the SOC. By analyzing the simulation results of constant discharge and pulsed variable current pulse discharge, it is proved that the filtering effect of adaptive UKF is better and the accuracy is higher.

Original language	English
Title of host publication	2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	137-140
Number of pages	4
ISBN (Electronic)	9781665443715
DOIs	https://doi.org/10.1109/REPE52765.2021.9617029
Publication status	Published - 2021
Externally published	Yes
Event	4th IEEE International Conference on Renewable Energy and Power Engineering, REPE 2021 - Virtual, Online, China Duration: 9 Oct 2021 → 11 Oct 2021

Publication series

Name	2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021

Conference

Conference	4th IEEE International Conference on Renewable Energy and Power Engineering, REPE 2021
Country/Territory	China
City	Virtual, Online
Period	9/10/21 → 11/10/21

UN SDGs

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

SDG 7 Affordable and Clean Energy

Free Keywords

Adaptive UKF
DSP
Lithium-ion batteries
State Of Charge

ASJC Scopus subject areas

Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Safety, Risk, Reliability and Quality
Control and Optimization

Access to Document

10.1109/REPE52765.2021.9617029

Cite this

Du, H., Liu, G., Zhang, J., Tian, G., & Wang, S. (2021). SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF. In 2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021 (pp. 137-140). (2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/REPE52765.2021.9617029

Du, Honggang ; Liu, Guangchen ; Zhang, Jianwei et al. / SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF. 2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 137-140 (2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021).

@inproceedings{0ac7a2ae164f4158935dae04db1b2206,

title = "SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF",

abstract = "Accurate estimation of the state of charge (SOC) of Lithium-ion batteries is the critical technology for developing Lithium-ion batteries. Aiming at the problem that the noise covariance of the UKF is fixed, an adaptive UKF algorithm is proposed in this paper. The adaptive UKF algorithm can estimate and correct the noise characteristics of the system in real-Time, and suppress the possible filter divergence and improve the estimation accuracy of the SOC. By analyzing the simulation results of constant discharge and pulsed variable current pulse discharge, it is proved that the filtering effect of adaptive UKF is better and the accuracy is higher.",

keywords = "Adaptive UKF, DSP, Lithium-ion batteries, State Of Charge",

author = "Honggang Du and Guangchen Liu and Jianwei Zhang and Guizhen Tian and Shengtie Wang",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 4th IEEE International Conference on Renewable Energy and Power Engineering, REPE 2021 ; Conference date: 09-10-2021 Through 11-10-2021",

year = "2021",

doi = "10.1109/REPE52765.2021.9617029",

language = "English",

series = "2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021",

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

pages = "137--140",

booktitle = "2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021",

address = "United States",

}

Du, H, Liu, G, Zhang, J, Tian, G & Wang, S 2021, SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF. in 2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021. 2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021, Institute of Electrical and Electronics Engineers Inc., pp. 137-140, 4th IEEE International Conference on Renewable Energy and Power Engineering, REPE 2021, Virtual, Online, China, 9/10/21. https://doi.org/10.1109/REPE52765.2021.9617029

SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF. / Du, Honggang; Liu, Guangchen; Zhang, Jianwei et al.
2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 137-140 (2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021).

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

TY - GEN

T1 - SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF

AU - Du, Honggang

AU - Liu, Guangchen

AU - Zhang, Jianwei

AU - Tian, Guizhen

AU - Wang, Shengtie

PY - 2021

Y1 - 2021

N2 - Accurate estimation of the state of charge (SOC) of Lithium-ion batteries is the critical technology for developing Lithium-ion batteries. Aiming at the problem that the noise covariance of the UKF is fixed, an adaptive UKF algorithm is proposed in this paper. The adaptive UKF algorithm can estimate and correct the noise characteristics of the system in real-Time, and suppress the possible filter divergence and improve the estimation accuracy of the SOC. By analyzing the simulation results of constant discharge and pulsed variable current pulse discharge, it is proved that the filtering effect of adaptive UKF is better and the accuracy is higher.

AB - Accurate estimation of the state of charge (SOC) of Lithium-ion batteries is the critical technology for developing Lithium-ion batteries. Aiming at the problem that the noise covariance of the UKF is fixed, an adaptive UKF algorithm is proposed in this paper. The adaptive UKF algorithm can estimate and correct the noise characteristics of the system in real-Time, and suppress the possible filter divergence and improve the estimation accuracy of the SOC. By analyzing the simulation results of constant discharge and pulsed variable current pulse discharge, it is proved that the filtering effect of adaptive UKF is better and the accuracy is higher.

KW - Adaptive UKF

KW - DSP

KW - Lithium-ion batteries

KW - State Of Charge

UR - https://www.scopus.com/pages/publications/85123475890

U2 - 10.1109/REPE52765.2021.9617029

DO - 10.1109/REPE52765.2021.9617029

M3 - Conference contribution

AN - SCOPUS:85123475890

T3 - 2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021

SP - 137

EP - 140

BT - 2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 4th IEEE International Conference on Renewable Energy and Power Engineering, REPE 2021

Y2 - 9 October 2021 through 11 October 2021

ER -

Du H, Liu G, Zhang J, Tian G, Wang S. SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF. In 2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 137-140. (2021 IEEE 4th International Conference on Renewable Energy and Power Engineering, REPE 2021). doi: 10.1109/REPE52765.2021.9617029

SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF

Abstract

Publication series

Conference

UN SDGs

Free Keywords

ASJC Scopus subject areas

Access to Document

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