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A novel data-driven method for mining battery open-circuit voltage characterization
Beijing Inst Technol, Sch Mech Engn, Adv Energy Storage & Applicat AESA Grp, Beijing 100081, Peoples R China..
Beijing Inst Technol, Sch Mech Engn, Adv Energy Storage & Applicat AESA Grp, Beijing 100081, Peoples R China..
Beijing Inst Technol, Sch Mech Engn, Adv Energy Storage & Applicat AESA Grp, Beijing 100081, Peoples R China..
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-6279-4446
2022 (English)In: GREEN ENERGY AND INTELLIGENT TRANSPORTATION, ISSN 2097-2512, Vol. 1, no 1, article id 100001Article in journal (Refereed) Published
Abstract [en]

Lithium-ion batteries (LiB) are widely used in electric vehicles (EVs) and battery energy storage systems, and accurate state estimation relying on the relationship between battery Open-Circuit-Voltage (OCV) and State-ofCharge (SOC) is the basis for their safe and efficient applications. To avoid the time-consuming lab test needed for obtaining OCV-SOC curves, this study proposes a data-driven universal method by using operation data collected onboard about the variation of OCV with ampere-hour (Ah). To guarantee high reliability, a series of constraints have been implemented. To verify the effectiveness of this method, the constructed OCV-SOC curves are used to estimate battery SOC and State-of-Health (SOH), which are compared with data from both lab tests and EV manufacturers. Results show that a higher accuracy can be achieved in the estimation of both SOC and SOH, for which the maximum deviations are less than 3.0% and 2.9% respectively.

Place, publisher, year, edition, pages
ELSEVIER , 2022. Vol. 1, no 1, article id 100001
Keywords [en]
Li -ion battery, OCV-SOC, State -of -charge, State -of -health, Operation data
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-66826DOI: 10.1016/j.geits.2022.100001ISI: 001223738900001Scopus ID: 2-s2.0-85159240756OAI: oai:DiVA.org:mdh-66826DiVA, id: diva2:1862374
Available from: 2024-05-29 Created: 2024-05-29 Last updated: 2024-05-29Bibliographically approved

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Li, Hailong

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