Cited by 191Advanced Battery Technologies ResearchAdvancements in Battery MaterialsReliability and Maintenance Optimization

Realistic lifetime prediction approach for Li-ion batteries

Sarasketa-Zabala, E., Martinez-Laserna, E., Berecibar, M., Gandiaga, I., Rodriguez-Martinez, L.M., Villarreal, I.·2016·Applied Energy

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Crossref · 10.1016/j.apenergy.2015.10.115

Cites

31 of 31 references verified0 citation errors · 0 not checkable

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  • Most existing studies model battery cyclic and calendar aging independently and combine the two to make predictions under a dynamic load profile.

    “Most of the existing studies model the battery cyclic and calendar aging independently, and combine the two to make predictions under a dynamic load profile [6,94,95].”

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Authors
Sarasketa-Zabala, E., Martinez-Laserna, E., Berecibar, M., Gandiaga, I., Rodriguez-Martinez, L. M., & Villarreal, I.
Affiliations
Ikerlan (ES)
Corresponding author
Sarasketa-Zabala, E.
Venue
Applied Energy
Publisher
Elsevier BV
Published
2016-01
Volume
162
Pages
839-852
ISSN
0306-2619 (ISSN-L)
OpenAlex
W2191802622
Cited by
191
References
31
Citations by year
2026: 6 · 2025: 14 · 2024: 22 · 2023: 25 · 2022: 12 · 2021: 24 · 2020: 30 · 2019: 28 · 2018: 16 · 2017: 7 · 2016: 7
FWCI
10.32
Type
journal article
Language
en
Open access
closed
Locations
  • Applied Energy (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • VUBIR (Vrije Universiteit Brussel) (submittedVersion)
Funders
ETORTEK
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
  • Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Reliability and Maintenance Optimization
Keywords
lithium-ion batteries, battery lifetime prediction, aging models, calendar aging, dynamic validation, model error analysis, lithium iron phosphate cells, vehicle-to-grid

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