Estimation of Depth of Discharge of Li-ion Battery Using Neural Network

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F21%3APU142040" target="_blank" >RIV/00216305:26220/21:PU142040 - isvavai.cz</a>
Result on the web
<a href="https://iopscience.iop.org/article/10.1149/10501.0541ecst" target="_blank" >https://iopscience.iop.org/article/10.1149/10501.0541ecst</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1149/10501.0541ecst" target="_blank" >10.1149/10501.0541ecst</a>

Result language
angličtina
Original language name
Estimation of Depth of Discharge of Li-ion Battery Using Neural Network
Original language description
This paper deals with the estimation of depth of discharge for Li-ion batteries. Estimation is based on the knowledge of discharging curves measured for discrete values of loading currents. The estimator of the depth of discharge is a form of feedforward neural network which is trained with the measured data of discharge curves. Accuracy of estimation of the depth of discharge is shown for arbitrary generated and measured loading characteristics, where the depth of discharge is estimated by the designed neural network and measured by using the Coulomb counting method.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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