Evidence map›Paper›PMID 33489267›Full record

ArticleRoyal Society open science2020

Linear parameter-varying model for a refuellable zinc-air battery.

Woranunt Lao-Atiman, Sorin Olaru, Sette Diop, Sigurd Skogestad, Amornchai Arpornwichanop, Rongrong Cheacharoen, Soorathep Kheawhom

Abstract read
In one paragraph

Article in Royal Society open science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Woranunt Lao-AtimanDepartment of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand.
Sorin OlaruCentraleSupélec, Laboratoire des signaux et systèmes, Université Paris-Saclay, CNRS, Gif sur Yvette, France.
Sette DiopCentraleSupélec, Laboratoire des signaux et systèmes, Université Paris-Saclay, CNRS, Gif sur Yvette, France.
Sigurd SkogestadDepartment of Chemical Engineering, Norwegian University of Science and Technology, Trondheim, Norway.
Amornchai ArpornwichanopDepartment of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand.
Rongrong CheacharoenMetallurgy and Materials Science Research Institute, Chulalongkorn University, Bangkok, Thailand.
Soorathep KheawhomDepartment of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand.ORCID 0000-0002-3129-2750

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the increasing trend of using renewable energy, the development of an energy storage system (ESS) attracts great research interest. A zinc-air battery (ZAB) is a promising ESS due to its high capacity, low cost and high potential to support circular economy principles. However, despite ZABs' technological advancements, a generic dynamic model for a ZAB, which is a key component for effective battery management and monitoring, is still lacking. ZABs show nonlinear behaviour where the steady-state gain is strongly dependent on operating conditions. The present study aims to develop a dynamic model, being capable of predicting the nonlinear dynamic behaviour of a refuellable ZAB, using a linear parameter-varying (LPV) technique. The LPV model is constructed from a family of linear time-invariant models, where the discharge current level is used as a scheduling parameter. The developed LPV model is benchmarked against linear and nonlinear model counterparts. Herein, the LPV model performs remarkably well in capturing the nonlinear behaviour of a ZAB. It significantly outperforms the linear model. Overall, the LPV approach provides a systematic way to construct a robust dynamic model which well represents the nonlinear behaviour of a ZAB.

Indexed as

dynamic modellinear modellinear parameter-varying modelnonlinear modelzinc–air battery

Identifiers

PMID33489267
PMCPMC7813229

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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.