Kalman-variant estimators for state of charge in lithium-sulfur batteries
Date
2022-05-01 01:10
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Cranfield University
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Citation
Propp, Karsten; Auger, Daniel; Fotouhi, Abbas; Longo, Stefano; Knap, Vaclav (2021). Kalman-variant estimators for state of charge in lithium-sulfur batteries. Cranfield Online Research Data (CORD). Dataset. https://doi.org/10.17862/cranfield.rd.3834057
Abstract
This fileset is a set of MATLAB/Simulink R2016a models implementing state-of-charge estimators for lithium-sulfur batteries as described in the associated publications. The associated experimental data is also included. Instructions are included in a 'readme.txt' file in the root directory.
This fileset is a set of MATLAB/Simulink R2016a models implementing state-of-charge estimators for lithium-sulfur batteries as described in the associated publications. The associated experimental data is also included. Instructions are included in a 'readme.txt' file in the root directory.
Description
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Github
Keywords
lithium-sulfur battery', 'state of charge', 'extended kalman filter', 'unscented kalman filter', 'particle filter', 'Engineering not elsewhere classified'
DOI
10.17862/cranfield.rd.3834057
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CC BY-NC-ND 4.0
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Funder/s
EP L505286/1