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State of Health Battery Algorithm for Real Applications. / Berecibar, Maitane; Omar, Noshin; Coosemans, Thierry; Van Mierlo, Joeri; Messagie, Maarten.

EVS31. The World Electric Vehicle Association (WEVA), 2018.

Research output: Chapter in Book/Report/Conference proceedingConference paperResearch

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Berecibar, M, Omar, N, Coosemans, T, Van Mierlo, J & Messagie, M 2018, State of Health Battery Algorithm for Real Applications. in EVS31. The World Electric Vehicle Association (WEVA), EVS31, Kobe, Japan, 30/09/18.

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BibTeX

@inproceedings{45e0b75564174ded8d4a04d54eb8b8f6,
title = "State of Health Battery Algorithm for Real Applications",
abstract = "An accurate model for State of Health estimation in Li-ion batteries is presented. This algorithm can address the state of health estimation at cell, module and battery pack level. An embeddable easy to implement algorithm has been verified and validated in a 79 different scenarios. The algorithm is based on detecting some features, which are easily measured from voltage measurements. The use of the algorithm is suitable to be implemented in different promising applications. Consequently, the algorhithm is also evaluated on this regard. In adittion, some modifications are suggested so to run the estimator quicker.",
keywords = "Lithium-ion, Battery Management System, Real applications, State of Health, Incremental capacity",
author = "Maitane Berecibar and Noshin Omar and Thierry Coosemans and {Van Mierlo}, Joeri and Maarten Messagie",
year = "2018",
month = "10",
day = "1",
language = "English",
booktitle = "EVS31",
publisher = "The World Electric Vehicle Association (WEVA)",

}

RIS

TY - GEN

T1 - State of Health Battery Algorithm for Real Applications

AU - Berecibar, Maitane

AU - Omar, Noshin

AU - Coosemans, Thierry

AU - Van Mierlo, Joeri

AU - Messagie, Maarten

PY - 2018/10/1

Y1 - 2018/10/1

N2 - An accurate model for State of Health estimation in Li-ion batteries is presented. This algorithm can address the state of health estimation at cell, module and battery pack level. An embeddable easy to implement algorithm has been verified and validated in a 79 different scenarios. The algorithm is based on detecting some features, which are easily measured from voltage measurements. The use of the algorithm is suitable to be implemented in different promising applications. Consequently, the algorhithm is also evaluated on this regard. In adittion, some modifications are suggested so to run the estimator quicker.

AB - An accurate model for State of Health estimation in Li-ion batteries is presented. This algorithm can address the state of health estimation at cell, module and battery pack level. An embeddable easy to implement algorithm has been verified and validated in a 79 different scenarios. The algorithm is based on detecting some features, which are easily measured from voltage measurements. The use of the algorithm is suitable to be implemented in different promising applications. Consequently, the algorhithm is also evaluated on this regard. In adittion, some modifications are suggested so to run the estimator quicker.

KW - Lithium-ion

KW - Battery Management System

KW - Real applications

KW - State of Health

KW - Incremental capacity

M3 - Conference paper

BT - EVS31

PB - The World Electric Vehicle Association (WEVA)

ER -

ID: 40154229