Random Forest-Based Grouping for Accurate SOH Estimation in Second-Life Batteries
Random Forest-Based Grouping for Accurate SOH Estimation in Second-Life Batteries
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Full title
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Publisher
Basel: MDPI AG
Journal title
Language
English
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Publication information
Publisher
Basel: MDPI AG
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Scope and Contents
Contents
Retired batteries pose a significant current and future challenge for electric mobility due to their high cost and the need for a state of health (SOH) above 80% to supply energy efficiently. Recycling and alternative applications are the primary options for these batteries, with recycling still undergoing research as regards more efficient and cos...
Alternative Titles
Full title
Random Forest-Based Grouping for Accurate SOH Estimation in Second-Life Batteries
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_6601296067874d3a9c08d81b1ea68960
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6601296067874d3a9c08d81b1ea68960
Other Identifiers
ISSN
2624-8921
E-ISSN
2624-8921
DOI
10.3390/vehicles6020038
