Evidence map›Paper›PMID 35539789›Full record

ArticleRSC advances2018

Capacity detection of electric vehicle lithium-ion batteries based on X-ray computed tomography.

Lifu Li, Junwei Hou

Abstract read
In one paragraph

Article in RSC advances, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Lifu LiSchool of Mechanical and Automotive Engineering, South China University of Technology Guangzhou 510640 China junweihou@foxmail.com.
Junwei HouSchool of Mechanical and Automotive Engineering, South China University of Technology Guangzhou 510640 China junweihou@foxmail.com.ORCID https://orcid.org/0000-0002-6860-2863

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is difficult to use conventional capacity detection methods to determine nondestructively and rapidly the capacity of lithium-ion (Li-ion) batteries used in electric vehicles. To resolve this problem, lithium iron phosphate (LFP) batteries are regarded as research objects for studying the relationship between their electrochemical performances and the structural parameters of their active materials based on Faraday's law. Therefore, a capacity detection method based on X-ray computed tomography is proposed; it combines the battery's electrochemical performance testing techniques and tomographic measurement techniques to measure the electrochemical properties and structural parameters of active materials of Li-ion batteries. The results show that (1) the capacity of a Li-ion battery is a function of the structural parameters of active materials and working condition; (2) the influence of the working condition on the capacity gradually changes with the change in the structural parameters of the active material; and (3) the loss of strong active materials of a Li-ion battery in the negative cross-section is more than that in the positive cross-section when the capacity decays. Owing to its advantages of being nondestructive and rapid, this method is superior compared with conventional methods.

Identifiers

PMID35539789
PMCPMC9082563

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.