Robust State of Health Estimation for Lithium-Ion Batteries Using Machines Learning

Xin Sui

doi:10.54337/aau466409590

Robust State of Health Estimation for Lithium-Ion Batteries Using Machines Learning

Research output: PhD thesis

227 Downloads (Pure)

Original language	English
Supervisors	Teodorescu, Remus, Principal supervisor Stroe, Daniel-Ioan, Co-supervisor
Publisher	Aalborg Universitetsforlag
Electronic ISBNs	978-87-7573-972-1
DOIs	https://doi.org/10.54337/aau466409590
Publication status	Published - 2021

Bibliographical note

PhD supervisor:
Prof. Remus Teodorescu, Aalborg University

Assistant PhD supervisor:
Assoc. Prof. Daniel-Ioan Stroe, Aalborg University

Keywords

Machine learning
Li-ion batteries
State of health estimation
Fuzzy entropy
Robust estimation

Access to Document

10.54337/aau466409590

PHD_XS_E-pdfFinal published version, 4.26 MB

AUB Link

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4 Journal article
1 Article in proceeding
1 Review article

A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery
Sui, X., He, S., Vilsen, S. B., Meng, J., Teodorescu, R. & Stroe, D-I., Oct 2021, In: Applied Energy. 300, 21 p., 117346.
Research output: Contribution to journal › Journal article › Research › peer-review

Open Access
File
183 Citations (Scopus)

324 Downloads (Pure)
Fast and Robust Estimation of Lithium-ion Batteries State of Health Using Ensemble Learning
Sui, X., He, S., Vilsen, S. B., Teodorescu, R. & Stroe, D-I., 16 Nov 2021, 2021 IEEE Energy Conversion Congress and Exposition (ECCE). p. 1393-1399 7 p. (IEEE Energy Conversion Congress and Exposition).
Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
5 Citations (Scopus)

8 Downloads (Pure)
Fuzzy Entropy-based State of Health Estimation for Li-Ion Batteries
Sui, X., He, S., Meng, J., Teodorescu, R. & Stroe, D-I., 2021, In: I E E E Journal of Emerging and Selected Topics in Power Electronics. 9, 4, p. 5125-5137 13 p., 9305691.
Research output: Contribution to journal › Journal article › Research › peer-review

Open Access
File
30 Citations (Scopus)

176 Downloads (Pure)

Cite this

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title = "Robust State of Health Estimation for Lithium-Ion Batteries Using Machines Learning",

keywords = "Machine learning, Li-ion batteries, State of health estimation, Fuzzy entropy, Robust estimation",

author = "Xin Sui",

note = "PhD supervisor: Prof. Remus Teodorescu, Aalborg University Assistant PhD supervisor: Assoc. Prof. Daniel-Ioan Stroe, Aalborg University",

year = "2021",

doi = "10.54337/aau466409590",

language = "English",

series = "Ph.d.-serien for Det Ingeni{\o}r- og Naturvidenskabelige Fakultet, Aalborg Universitet",

publisher = "Aalborg Universitetsforlag",

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TY - GEN

T1 - Robust State of Health Estimation for Lithium-Ion Batteries Using Machines Learning

AU - Sui, Xin

N1 - PhD supervisor: Prof. Remus Teodorescu, Aalborg University Assistant PhD supervisor: Assoc. Prof. Daniel-Ioan Stroe, Aalborg University

PY - 2021

Y1 - 2021

KW - Machine learning

KW - Li-ion batteries

KW - State of health estimation

KW - Fuzzy entropy

KW - Robust estimation

U2 - 10.54337/aau466409590

DO - 10.54337/aau466409590

M3 - PhD thesis

T3 - Ph.d.-serien for Det Ingeniør- og Naturvidenskabelige Fakultet, Aalborg Universitet

PB - Aalborg Universitetsforlag

ER -

Robust State of Health Estimation for Lithium-Ion Batteries Using Machines Learning

Bibliographical note

Keywords

Access to Document

AUB Link

Research output

A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery

Fast and Robust Estimation of Lithium-ion Batteries State of Health Using Ensemble Learning

Fuzzy Entropy-based State of Health Estimation for Li-Ion Batteries

Cite this