Lithium-Ion Battery State-of-Health Estimation Using the Incremental Capacity Analysis Technique

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Resumé

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 calendar aging results collected during eleven months of testing, we were able to relate the capacity fade of the studied batteries to the evolution of four metric points, which were obtained using the ICA. Furthermore, the accuracy of the proposed models for capacity fade and SOH estimation was successfully verified considering two different aging conditions.
OriginalsprogEngelsk
TidsskriftI E E E Transactions on Industry Applications
Vol/bind56
Udgave nummer1
Sider (fra-til)678 - 685
Antal sider8
ISSN0093-9994
DOI'er
PublikationsstatusAccepteret/In press - 2020

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Health
Electric vehicles
Aging of materials
Testing
Lithium-ion batteries
Battery management systems

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title = "Lithium-Ion Battery State-of-Health Estimation Using the Incremental Capacity Analysis Technique",
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 calendar aging results collected during eleven months of testing, we were able to relate the capacity fade of the studied batteries to the evolution of four metric points, which were obtained using the ICA. Furthermore, the accuracy of the proposed models for capacity fade and SOH estimation was successfully verified considering two different aging conditions.",
keywords = "Lithium-ion Battery, SOH Estimation, Electric Vehicle, Incremental Capacity Analysis",
author = "Daniel-Ioan Stroe and Erik Schaltz",
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Lithium-Ion Battery State-of-Health Estimation Using the Incremental Capacity Analysis Technique. / Stroe, Daniel-Ioan; Schaltz, Erik.

i: I E E E Transactions on Industry Applications, Bind 56, Nr. 1, 2020, s. 678 - 685.

Eksport af forskningsdata: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

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AU - Schaltz, Erik

PY - 2020

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AB - 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 calendar aging results collected during eleven months of testing, we were able to relate the capacity fade of the studied batteries to the evolution of four metric points, which were obtained using the ICA. Furthermore, the accuracy of the proposed models for capacity fade and SOH estimation was successfully verified considering two different aging conditions.

KW - Lithium-ion Battery

KW - SOH Estimation

KW - Electric Vehicle

KW - Incremental Capacity Analysis

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JO - I E E E Transactions on Industry Applications

JF - I E E E Transactions on Industry Applications

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