Evidence map›Paper›PMID 33671244›Full record

ReviewSensors (Basel, Switzerland)2021

Fiber Optic Sensing Technologies for Battery Management Systems and Energy Storage Applications.

Yang D Su, Yuliya Preger, Hannah Burroughs, Chenhu Sun, Paul R Ohodnicki

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

5 authors.

Yang D SuMechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA 15260, USA.
Yuliya PregerSandia National Laboratories, Albuquerque, NM 87123, USA.ORCID 0000-0001-8558-2529
Hannah BurroughsLawrence Livermore National Laboratory, Livermore, CA 94550, USA.
Chenhu SunMechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA 15260, USA.
Paul R OhodnickiMechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA 15260, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Applications of fiber optic sensors to battery monitoring have been increasing due to the growing need of enhanced battery management systems with accurate state estimations. The goal of this review is to discuss the advancements enabling the practical implementation of battery internal parameter measurements including local temperature, strain, pressure, and refractive index for general operation, as well as the external measurements such as temperature gradients and vent gas sensing for thermal runaway imminent detection. A reasonable matching is discussed between fiber optic sensors of different range capabilities with battery systems of three levels of scales, namely electric vehicle and heavy-duty electric truck battery packs, and grid-scale battery systems. The advantages of fiber optic sensors over electrical sensors are discussed, while electrochemical stability issues of fiber-implanted batteries are critically assessed. This review also includes the estimated sensing system costs for typical fiber optic sensors and identifies the high interrogation cost as one of the limitations in their practical deployment into batteries. Finally, future perspectives are considered in the implementation of fiber optics into high-value battery applications such as grid-scale energy storage fault detection and prediction systems.

Indexed as

battery management systemscost estimationelectric vehiclefiber Bragg gratingfiber optic sensorLi-ion batterytemperature monitoringthermal runaway

Identifiers

PMID33671244
PMCPMC7923102

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.