State of Health Estimation for Lithium-ion Battery Using Fuzzy Entropy and Support Vector Machine

Xin Sui; Shan He; Daniel-Ioan Stroe; Remus Teodorescu

doi:10.1109/IPEMC-ECCEAsia48364.2020.9368182

State of Health Estimation for Lithium-ion Battery Using Fuzzy Entropy and Support Vector Machine

Xin Sui, Shan He, Daniel-Ioan Stroe, Remus Teodorescu

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

6 Citationer (Scopus)

Abstract

In this paper, fuzzy entropy (FE), as a new feature, is applied for LiFeO4 battery state of health (SOH) estimation. Compared with sample entropy, FE introduces the exponential function to measure the similarity of voltage vectors and the mean of the match templates is removed. As a result, FE can capture the variation of voltage during the battery degradation more efficiently in terms of the parameter selection, data noise, and data size. Then the FE-SOH mapping is established by combining FE with support vector machine, and the effectiveness of the proposed method is verified by experimental results.

Originalsprog	Engelsk
Titel	2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC 2020-ECCE Asia)
Antal sider	6
Forlag	IEEE
Publikationsdato	2020
Sider	1417-1422
Artikelnummer	9368182
ISBN (Trykt)	978-1-7281-5302-5
ISBN (Elektronisk)	978-1-7281-5301-8
DOI	https://doi.org/10.1109/IPEMC-ECCEAsia48364.2020.9368182
Status	Udgivet - 2020
Begivenhed	2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC2020-ECCE Asia) - Nanjing, Kina Varighed: 29 nov. 2020 → 2 dec. 2020

Konference

Konference	2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC2020-ECCE Asia)
Land/Område	Kina
By	Nanjing
Periode	29/11/2020 → 02/12/2020

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10.1109/IPEMC-ECCEAsia48364.2020.9368182

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Citationsformater

@inproceedings{454cac8a91cf498cb33c84b78e7aa2e9,

title = "State of Health Estimation for Lithium-ion Battery Using Fuzzy Entropy and Support Vector Machine",

abstract = "In this paper, fuzzy entropy (FE), as a new feature, is applied for LiFeO4 battery state of health (SOH) estimation. Compared with sample entropy, FE introduces the exponential function to measure the similarity of voltage vectors and the mean of the match templates is removed. As a result, FE can capture the variation of voltage during the battery degradation more efficiently in terms of the parameter selection, data noise, and data size. Then the FE-SOH mapping is established by combining FE with support vector machine, and the effectiveness of the proposed method is verified by experimental results.",

keywords = "Lithium-ion batteries, fuzzy entropy, sample entropy, state of health, support vector machine",

author = "Xin Sui and Shan He and Daniel-Ioan Stroe and Remus Teodorescu",

year = "2020",

doi = "10.1109/IPEMC-ECCEAsia48364.2020.9368182",

language = "English",

isbn = "978-1-7281-5302-5",

pages = "1417--1422",

booktitle = "2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC 2020-ECCE Asia)",

publisher = "IEEE",

address = "United States",

note = "2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC2020-ECCE Asia) ; Conference date: 29-11-2020 Through 02-12-2020",

}

Sui, X , He, S , Stroe, D-I & Teodorescu, R 2020, State of Health Estimation for Lithium-ion Battery Using Fuzzy Entropy and Support Vector Machine. i 2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC 2020-ECCE Asia)., 9368182, IEEE, s. 1417-1422, 2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC2020-ECCE Asia), Nanjing, Kina, 29/11/2020. https://doi.org/10.1109/IPEMC-ECCEAsia48364.2020.9368182

State of Health Estimation for Lithium-ion Battery Using Fuzzy Entropy and Support Vector Machine. / Sui, Xin ; He, Shan ; Stroe, Daniel-Ioan et al.
2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC 2020-ECCE Asia). IEEE, 2020. s. 1417-1422 9368182.

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

T1 - State of Health Estimation for Lithium-ion Battery Using Fuzzy Entropy and Support Vector Machine

AU - Sui, Xin

AU - He, Shan

AU - Stroe, Daniel-Ioan

AU - Teodorescu, Remus

PY - 2020

Y1 - 2020

N2 - In this paper, fuzzy entropy (FE), as a new feature, is applied for LiFeO4 battery state of health (SOH) estimation. Compared with sample entropy, FE introduces the exponential function to measure the similarity of voltage vectors and the mean of the match templates is removed. As a result, FE can capture the variation of voltage during the battery degradation more efficiently in terms of the parameter selection, data noise, and data size. Then the FE-SOH mapping is established by combining FE with support vector machine, and the effectiveness of the proposed method is verified by experimental results.

AB - In this paper, fuzzy entropy (FE), as a new feature, is applied for LiFeO4 battery state of health (SOH) estimation. Compared with sample entropy, FE introduces the exponential function to measure the similarity of voltage vectors and the mean of the match templates is removed. As a result, FE can capture the variation of voltage during the battery degradation more efficiently in terms of the parameter selection, data noise, and data size. Then the FE-SOH mapping is established by combining FE with support vector machine, and the effectiveness of the proposed method is verified by experimental results.

KW - Lithium-ion batteries

KW - fuzzy entropy

KW - sample entropy

KW - state of health

KW - support vector machine

UR - http://www.scopus.com/inward/record.url?scp=85103218135&partnerID=8YFLogxK

U2 - 10.1109/IPEMC-ECCEAsia48364.2020.9368182

DO - 10.1109/IPEMC-ECCEAsia48364.2020.9368182

M3 - Article in proceeding

SN - 978-1-7281-5302-5

SP - 1417

EP - 1422

BT - 2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC 2020-ECCE Asia)

PB - IEEE

T2 - 2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC2020-ECCE Asia)

Y2 - 29 November 2020 through 2 December 2020

ER -

State of Health Estimation for Lithium-ion Battery Using Fuzzy Entropy and Support Vector Machine

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