Cited by 131Electric and Hybrid Vehicle TechnologiesVehicle emissions and performanceElectric Vehicles and Infrastructure

The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.

Health-conscious deep reinforcement learning energy management for fuel cell buses integrating environmental and look-ahead road information

Overview

Integrity signals

Registry

Crossref · 10.1016/j.energy.2023.130146

Cites

38 of 38 references verified0 citation errors · 0 not checkable

Statistics

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

Verification

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?

Citations

Cites

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Metadata

Authors
Jia, C., Zhou, J., He, H., Li, J., Wei, Z., & Li, K.
Affiliations
  • Beijing Institute of Technology (CN)
  • Weifang University of Science and Technology (CN)
Corresponding author
He, Hongwen
Venue
Energy
Publisher
Elsevier BV
Published
2024-03
Volume
290
Pages
130146
ISSN
0360-5442 (ISSN-L)
OpenAlex
W4390277060
Cited by
131
References
37
Citations by year
2026: 37 · 2025: 48 · 2024: 46
FWCI
9.52
Type
journal article
Language
en
Open access
closed
Locations
  • Energy (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
  • Physical Sciences › Engineering › Automotive Engineering › Vehicle emissions and performance
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
Keywords
energy management strategy, deep reinforcement learning, TD3, fuel cell durability, environmental factors, driving conditions, battery life

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.

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