Cited by 199Advanced Battery Technologies ResearchAdvancements in Battery MaterialsReliability and Maintenance Optimization

A novel prediction method based on the support vector regression for the remaining useful life of lithium-ion batteries

Zhao, Qi, Qin, Xiaoli, Zhao, Hongbo, Feng, Wenquan·2018·Microelectronics Reliability

Integrity signals

Registry

Crossref · 10.1016/j.microrel.2018.04.007

Cites

26 of 26 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Zhao, Q., Qin, X., Zhao, H., & Feng, W.
Affiliations
Beihang University (CN)
Corresponding author
Zhao, Hongbo
Venue
Microelectronics Reliability
Publisher
Elsevier BV
Published
2018-06
Volume
85
Pages
99-108
ISSN
0026-2714 (ISSN-L)
OpenAlex
W2799353157
Cited by
199
References
26
Citations by year
2026: 11 · 2025: 33 · 2024: 33 · 2023: 35 · 2022: 28 · 2021: 28 · 2020: 15 · 2019: 15 · 2018: 1
FWCI
7.83
Type
journal article
Language
en
Open access
closed
Locations
Microelectronics Reliability (publishedVersion)
Funders
Aerospace Innovation Fund (20160357)
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, remaining useful life prediction, state of health estimation, battery prognostics, support vector regression, feature vector selection, capacity fade, health indicators

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review