Capacity loss estimation for li-ion batteries based on a semi-empirical model

dc.contributor.authorRabah Mohammed
dc.contributor.authorImmonen Eero
dc.contributor.authorShahsavari Sajad
dc.contributor.authorHaghbayan Mohammad-Hashem
dc.contributor.authorMurashko Kirill
dc.contributor.authorImmonen Paula
dc.contributor.organizationfi=robotiikka ja autonomiset järjestelmät|en=Robotics and Autonomous Systems|
dc.contributor.organizationfi=tietotekniikan laitos|en=Department of Computing|
dc.contributor.organization-code1.2.246.10.2458963.20.72785230805
dc.contributor.organization-code1.2.246.10.2458963.20.85312822902
dc.converis.publication-id66341359
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/66341359
dc.date.accessioned2022-10-28T13:13:33Z
dc.date.available2022-10-28T13:13:33Z
dc.description.abstract<p>Understanding battery capacity degradation is instrumental for designing modern electric vehicles. In this paper, a Semi-Empirical Model for predicting the Capacity Loss of Lithium-ion batteries during Cycling and Calendar Aging is developed. In order to redict the Capacity Loss with a high accuracy, battery operation data from different test conditions and different Lithium-ion batteries chemistries were obtained from literature for parameter optimization (fitting). The obtained models were then compared to experimental data for validation. Our results show that the average error between the estimated Capacity Loss and measured Capacity Loss is less than 1.5% during Cycling Aging, and less than 2% during Calendar Aging. An electric mining dumper, with simulated duty cycle data, is considered as an application example.<br></p>
dc.format.pagerange235
dc.format.pagerange242
dc.identifier.isbn978-3-937436-72-2
dc.identifier.issn2522-2414
dc.identifier.jour-issn2522-2414
dc.identifier.olddbid180617
dc.identifier.oldhandle10024/163711
dc.identifier.urihttps://www.utupub.fi/handle/11111/32173
dc.identifier.urlhttp://www.scs-europe.net/dlib/2021/ecms2021acceptedpapers/0235_simo_ecms2021_0036.pdf
dc.identifier.urnURN:NBN:fi-fe2022012710856
dc.language.isoen
dc.okm.affiliatedauthorHaghbayan, Hashem
dc.okm.affiliatedauthorShahsavari, Sajad
dc.okm.discipline213 Electronic, automation and communications engineering, electronicsen_GB
dc.okm.discipline213 Sähkö-, automaatio- ja tietoliikennetekniikka, elektroniikkafi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA4 Conference Article
dc.publisher.countryUnited Kingdomen_GB
dc.publisher.countryBritanniafi_FI
dc.publisher.country-codeGB
dc.relation.conferenceEuropean Conference on Modelling and Simulation
dc.relation.doi10.7148/2021-0235
dc.relation.ispartofjournalProceedings: European Conference for Modelling and Simulation
dc.relation.ispartofseriesCommunications of the ECMS
dc.relation.volume1
dc.relation.volume35
dc.source.identifierhttps://www.utupub.fi/handle/10024/163711
dc.titleCapacity loss estimation for li-ion batteries based on a semi-empirical model
dc.title.bookProceedings of the 35th ECMS International Conference on Modelling and Simulation ECMS 2021
dc.year.issued2021

Tiedostot

Näytetään 1 - 1 / 1
Ladataan...
Name:
0235_simo_ecms2021_0036.pdf
Size:
2.89 MB
Format:
Adobe Portable Document Format
Description:
Publisher's PDF