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http://hdl.handle.net/1942/40602
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DC Field | Value | Language |
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dc.contributor.author | HAMED, Hamid | - |
dc.contributor.author | Yusuf, Marwan | - |
dc.contributor.author | Suliga, Marek | - |
dc.contributor.author | GHALAMI CHOOBAR, Behnam | - |
dc.contributor.author | Kostos, Ryan | - |
dc.contributor.author | SAFARI, Momo | - |
dc.date.accessioned | 2023-07-14T14:46:57Z | - |
dc.date.available | 2023-07-14T14:46:57Z | - |
dc.date.issued | 2023 | - |
dc.date.submitted | 2023-07-06T07:42:05Z | - |
dc.identifier.citation | Batteries & Supercaps, (Art N° e202300140) | - |
dc.identifier.uri | http://hdl.handle.net/1942/40602 | - |
dc.description.abstract | The Incremental Capacity (IC) is a rich source of data for the state-of-health estimation of lithium-ion batteries. This data is typically collected during a low C-rate (dis)charge of the battery which is not representative of many real-world applications outside the research laboratories. Here, this limitation is showcased to be mitigated by employing a new feature-extraction technique applied to a large dataset including 105 batteries with cycle lives ranging from 158 to 1637 cycles. The state-of-health of these batteries is successfully predicted with a mean-absolute-percentage error below 0.7 % by using three regression models of support vector regressor, multi-layer perceptron, and random forest. The methodologies proposed in this work facilitate the development of accurate IC-based state-of-health predictors for lithium-ion batteries in on-board applications. | - |
dc.language.iso | en | - |
dc.publisher | WILEY-V C H VERLAG GMBH | - |
dc.subject.other | battery | - |
dc.subject.other | incremental capacity | - |
dc.subject.other | state of health | - |
dc.title | An Incremental Capacity Analysis‐based State‐of‐health Estimation Model for Lithium‐ion Batteries in High‐power Applications | - |
dc.type | Journal Contribution | - |
local.bibliographicCitation.jcat | A1 | - |
local.publisher.place | POSTFACH 101161, 69451 WEINHEIM, GERMANY | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
local.bibliographicCitation.status | Early view | - |
local.bibliographicCitation.artnr | e202300140 | - |
local.type.programme | H2020 | - |
local.relation.h2020 | 963603 | - |
dc.identifier.doi | 10.1002/batt.202300140 | - |
dc.identifier.isi | WOS:001011873900001 | - |
local.provider.type | Web of Science | - |
local.uhasselt.international | no | - |
item.accessRights | Open Access | - |
item.fullcitation | HAMED, Hamid; Yusuf, Marwan; Suliga, Marek; GHALAMI CHOOBAR, Behnam; Kostos, Ryan & SAFARI, Momo (2023) An Incremental Capacity Analysis‐based State‐of‐health Estimation Model for Lithium‐ion Batteries in High‐power Applications. In: Batteries & Supercaps, (Art N° e202300140). | - |
item.fulltext | With Fulltext | - |
item.contributor | HAMED, Hamid | - |
item.contributor | Yusuf, Marwan | - |
item.contributor | Suliga, Marek | - |
item.contributor | GHALAMI CHOOBAR, Behnam | - |
item.contributor | Kostos, Ryan | - |
item.contributor | SAFARI, Momo | - |
crisitem.journal.eissn | 2566-6223 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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Batteries Supercaps - 2023 - Hamed - An Incremental Capacity Analysis‐based State‐of‐health Estimation Model for.pdf | Early view | 2.11 MB | Adobe PDF | View/Open |
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