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Abstract
The implementation of an accurate but also low computational demanding state-of-health (SOH) estimation algorithm represents a key challenge for the battery management systems in electric vehicle (EV) applications. In this paper we investigate the suitability of the incremental capacity analysis (ICA) technique for estimating the capacity fade and subsequently the SOH of LMO/NMC-based EV Lithium-ion batteries. Based on ageing results collected during eleven months of testing, we were able to accurately relate the capacity fade of the studied batteries to the evolution of the voltage value, which corresponds to one of the incremental capacity (IC) valleys, obtained using the ICA technique.
Originalsprog | Engelsk |
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Titel | Proceedings of the 2018 IEEE Energy Conversion Congress and Exposition (ECCE) |
Antal sider | 6 |
Forlag | IEEE Press |
Publikationsdato | sep. 2018 |
Sider | 2720-2725 |
ISBN (Trykt) | 978-1-4799-7313-2 |
ISBN (Elektronisk) | 978-1-4799-7312-5 |
DOI | |
Status | Udgivet - sep. 2018 |
Begivenhed | IEEE Energy Conversion Congress & Exposition ECCE 2018 - Portland, USA Varighed: 23 sep. 2018 → 27 sep. 2018 http://www.ieee-ecce.org/2018/ |
Konference
Konference | IEEE Energy Conversion Congress & Exposition ECCE 2018 |
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Land/Område | USA |
By | Portland |
Periode | 23/09/2018 → 27/09/2018 |
Internetadresse |
Navn | IEEE Energy Conversion Congress and Exposition |
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ISSN | 2329-3721 |
Fingeraftryk
Dyk ned i forskningsemnerne om 'SOH Estimation of LMO/NMC-based Electric Vehicle Lithium-Ion Batteries Using the Incremental Capacity Analysis Technique'. Sammen danner de et unikt fingeraftryk.Projekter
- 1 Afsluttet
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Batnostic: adaptive BATtery diagNOSTIC tools for lifetime assessment of EV batteries
01/01/2016 → 31/12/2018
Projekter: Projekt › Forskning