Li-ion Battery Pack State-of-Charge Estimation Disturbed by Colored Noises

Ximing Cheng; Shouqun Wang; Liguang Yao

doi:10.1016/j.egypro.2017.03.871

Li-ion Battery Pack State-of-Charge Estimation Disturbed by Colored Noises

Ximing Cheng^*
, Shouqun Wang
, Liguang Yao

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

Research output: Contribution to journal › Conference article › peer-review

9 Citations (Scopus)

Abstract

In electric vehicles, onboard lithium-ion batteries need an accurate state of charge (SOC) to enhance safety, improve efficiency, and extend lifetime. However, there are noises to disturb electric quantities of batteries, especially the battery current for SOC calculation. Based on an equivalent circuit model, the battery SOC is well estimated by a residua-sequence-based adaptive extended Kalman filter (AEKF) when the battery current is polluted by colored noises. This adaptive filtering technique was implemented on the experiment data of a real lithium-ion battery pack, the current values of which were contaminated by the non-zero mean Gaussian noise. Results showed that the SOC estimation produced by the proposed AEKF was much more accurate and reliable than that caused by the conventional extended Kalman filter (EKF) in the colored noise environment.

Original language	English
Pages (from-to)	4104-4109
Number of pages	6
Journal	Energy Procedia
Volume	105
DOIs	https://doi.org/10.1016/j.egypro.2017.03.871
Publication status	Published - 2017
Event	8th International Conference on Applied Energy, ICAE 2016 - Beijing, China Duration: 8 Oct 2016 → 11 Oct 2016

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Adaptive filter
Colored noises
Kalaman filters
Li-ion battery
State-of-charge (SOC)

Access to Document

10.1016/j.egypro.2017.03.871

Cite this

@article{369f5c0896fd4e02af9662384a2a4e50,

title = "Li-ion Battery Pack State-of-Charge Estimation Disturbed by Colored Noises",

abstract = "In electric vehicles, onboard lithium-ion batteries need an accurate state of charge (SOC) to enhance safety, improve efficiency, and extend lifetime. However, there are noises to disturb electric quantities of batteries, especially the battery current for SOC calculation. Based on an equivalent circuit model, the battery SOC is well estimated by a residua-sequence-based adaptive extended Kalman filter (AEKF) when the battery current is polluted by colored noises. This adaptive filtering technique was implemented on the experiment data of a real lithium-ion battery pack, the current values of which were contaminated by the non-zero mean Gaussian noise. Results showed that the SOC estimation produced by the proposed AEKF was much more accurate and reliable than that caused by the conventional extended Kalman filter (EKF) in the colored noise environment.",

keywords = "Adaptive filter, Colored noises, Kalaman filters, Li-ion battery, State-of-charge (SOC)",

author = "Ximing Cheng and Shouqun Wang and Liguang Yao",

note = "Publisher Copyright: {\textcopyright} 2017 The Authors. Published by Elsevier Ltd.; 8th International Conference on Applied Energy, ICAE 2016 ; Conference date: 08-10-2016 Through 11-10-2016",

year = "2017",

doi = "10.1016/j.egypro.2017.03.871",

language = "English",

volume = "105",

pages = "4104--4109",

journal = "Energy Procedia",

issn = "1876-6102",

publisher = "Elsevier Ltd.",

}

TY - JOUR

T1 - Li-ion Battery Pack State-of-Charge Estimation Disturbed by Colored Noises

AU - Cheng, Ximing

AU - Wang, Shouqun

AU - Yao, Liguang

PY - 2017

Y1 - 2017

N2 - In electric vehicles, onboard lithium-ion batteries need an accurate state of charge (SOC) to enhance safety, improve efficiency, and extend lifetime. However, there are noises to disturb electric quantities of batteries, especially the battery current for SOC calculation. Based on an equivalent circuit model, the battery SOC is well estimated by a residua-sequence-based adaptive extended Kalman filter (AEKF) when the battery current is polluted by colored noises. This adaptive filtering technique was implemented on the experiment data of a real lithium-ion battery pack, the current values of which were contaminated by the non-zero mean Gaussian noise. Results showed that the SOC estimation produced by the proposed AEKF was much more accurate and reliable than that caused by the conventional extended Kalman filter (EKF) in the colored noise environment.

AB - In electric vehicles, onboard lithium-ion batteries need an accurate state of charge (SOC) to enhance safety, improve efficiency, and extend lifetime. However, there are noises to disturb electric quantities of batteries, especially the battery current for SOC calculation. Based on an equivalent circuit model, the battery SOC is well estimated by a residua-sequence-based adaptive extended Kalman filter (AEKF) when the battery current is polluted by colored noises. This adaptive filtering technique was implemented on the experiment data of a real lithium-ion battery pack, the current values of which were contaminated by the non-zero mean Gaussian noise. Results showed that the SOC estimation produced by the proposed AEKF was much more accurate and reliable than that caused by the conventional extended Kalman filter (EKF) in the colored noise environment.

KW - Adaptive filter

KW - Colored noises

KW - Kalaman filters

KW - Li-ion battery

KW - State-of-charge (SOC)

UR - https://www.scopus.com/pages/publications/85020734186

U2 - 10.1016/j.egypro.2017.03.871

DO - 10.1016/j.egypro.2017.03.871

M3 - Conference article

AN - SCOPUS:85020734186

SN - 1876-6102

VL - 105

SP - 4104

EP - 4109

JO - Energy Procedia

JF - Energy Procedia

T2 - 8th International Conference on Applied Energy, ICAE 2016

Y2 - 8 October 2016 through 11 October 2016

ER -

Li-ion Battery Pack State-of-Charge Estimation Disturbed by Colored Noises

Abstract

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this