Assessment Method for Residual Value of Lead-acid Batteries Based on PAM Clustering Algorithm

Xuesong FENG, Xiaokun ZHANG, Yong XIANG*

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

1 Citation (Scopus)

Abstract

As the residual value of the lead-acid batteries is not effectively evaluated in the current scraping and recycling processes of the lead-acid batteries, the partition around medoids (PAM) clustering algorithm is adopted, and the scraped lead-acid batteries are classified with the changes in the temperature and charge-discharge occurring when the lead-acid batteries are in service as the characteristic parameters. Besides, the validity of the algorithm is validated using 300 lead-acid battery packs to be scrapped at the communication base station, from which the results showed that the residual value of the lead-acid batteries can be effectively distinguished by the partition around medoids algorithm according to the temperature and charge-discharge characteristic parameters.

Original languageEnglish
Article number032011
Number of pages6
JournalJournal of Physics: Conference Series
Volume1549
Issue number3
Early online date29 Jun 2020
DOIs
Publication statusPublished - Jun 2020
Externally publishedYes
Event2020 International Conference on Environment Science and Advanced Energy Technologies, ESAET 2020 - Chongqing, China
Duration: 18 Jan 202019 Jan 2020

Bibliographical note

Publisher Copyright:
© Published under licence by IOP Publishing Ltd.

Fingerprint

Dive into the research topics of 'Assessment Method for Residual Value of Lead-acid Batteries Based on PAM Clustering Algorithm'. Together they form a unique fingerprint.

Cite this