Cited by 363Advanced Battery Technologies ResearchElectric Vehicles and InfrastructureElectric and Hybrid Vehicle Technologies

Quantifying EV battery end-of-life through analysis of travel needs with vehicle powertrain models

Open access
Saxena, Samveg, Le Floch, Caroline, MacDonald, Jason, Moura, Scott·2015·Journal of Power Sources

Abstract

Electric vehicles enable clean and efficient transportation, however concerns about range anxiety and battery degradation hinder EV adoption. The common definition for battery end-of-life is when 70–80% of original energy capacity remains, however little analysis is available to support this retirement threshold. By applying detailed physics-based models of EVs with data on how drivers use their cars, we show that EV batteries continue to meet daily travel needs of drivers well beyond capacity fade of 80% remaining energy storage capacity. Further, we show that EV batteries with substantial energy capacity fade continue to provide sufficient buffer charge for unexpected trips with long distances. We show that enabling charging in more locations, even if only with 120 V wall outlets, prolongs useful life of EV batteries. Battery power fade is also examined and we show EVs meet performance requirements even down to 30% remaining power capacity. Our findings show that defining battery retirement at 70–80% remaining capacity is inaccurate. Battery retirement should instead be governed by when batteries no longer satisfy daily travel needs of a driver. Using this alternative retirement metric, we present results on the fraction of EV batteries that may be retired with different levels of energy capacity fade.

Integrity signals

Registry

Crossref · 10.1016/j.jpowsour.2015.01.072

Cites

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?

No citation lists for this paper

No citation lists for this paper yet — checked again daily.

References 27 · Cited by 363

Authors
Saxena, S., Le Floch, C., MacDonald, J., & Moura, S.
Affiliations
  • Lawrence Berkeley National Laboratory (US)
  • University of California, Berkeley (US)
Corresponding author
Saxena, Samveg
Venue
Journal of Power Sources
Publisher
Elsevier BV
Published
2015-05
Volume
282
Pages
265-276
ISSN
0378-7753 (ISSN-L)
OpenAlex
W2067437271
Cited by
363
References
27
Citations by year
2026: 26 · 2025: 36 · 2024: 41 · 2023: 38 · 2022: 37 · 2021: 38 · 2020: 38 · 2019: 34 · 2018: 28 · 2017: 19 · 2016: 18 · 2015: 10
FWCI
25.82
Type
journal article
Language
en
Open access
Locations
  • Journal of Power Sources (publishedVersion, cc-by)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
Funders
  • Lawrence Berkeley National Laboratory
  • Office of Science
  • U.S. Department of Energy
  • Laboratory Directed Research and Development
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
  • Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
Keywords
electric vehicle batteries, battery end-of-life, travel needs, vehicle powertrain modeling, charging infrastructure, range anxiety, battery degradation

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