{
  "abstract": "Early fault warning in lithium-ion battery packs is challenged by weak labels and changing operating conditions. This study combines cell-wise Local Outlier Factor (LOF) scoring with validity-gated Streaming Peaks-Over-Threshold (SPOT). Five descriptors are used to summarize each seven-sample median-centered voltage trajectory, and the maximum cell LOF is logarithmically transformed into a pack score. A generalized Pareto distribution (GPD) supplies the threshold when calibration diagnostics support the fitted tail; otherwise, an empirical quantile is used. Across nine real-world vehicles and six AI-generated CH-BatteryGen cases, 12 streams retain GPD-SPOT and three use the empirical fallback. At a target risk parameter q = 0.01, aggregate false-alarm rates are 1.85% for pre-event baselines and 1.64% for independent normal vehicles. Seven recorded field events have an alarm within the preceding 24 h, with a median lead time of 17.39 h. However, car10 provides only 0.053 h of notice, and window-level recall is 0.029 under broad ±24 h event labels. The supplied faulty cell ranks first in all three labeled lithium iron phosphate cases. The workflow provides statistical fault warnings and suspicious-cell rankings without fault-labeled model training.",
  "abstract_shown": true,
  "affiliations": [
    "Hangzhou Xili Intelligent Technology Co., Ltd., Hangzhou 310024, China",
    "School of Materials and Energy, University of Electronic Science and Technology of China, Chengdu 611731, China",
    "School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Xing Yang"
    },
    {
      "affs": [
        1
      ],
      "name": "Ziqiang Zhang"
    },
    {
      "affs": [
        2
      ],
      "name": "Zhili Qin",
      "orcid": "0009-0004-8030-9522"
    },
    {
      "affs": [
        1
      ],
      "name": "Baihai Li",
      "orcid": "0000-0002-9266-1791"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6jfzg7tv2vjqg.bib",
  "cited_by": 0,
  "doi": "10.3390/batteries12100415",
  "fulltext_url": null,
  "id": "6jfzg7tv2vjqg",
  "issns": [
    "2313-0105"
  ],
  "landing_url": "https://www.mdpi.com/2313-0105/12/10/415",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2203|Advanced Battery Technologies Research"
    ]
  ],
  "openalex": "W7221320116",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-10",
  "publisher": "MDPI AG",
  "ris": "https://research.draconitic.com/paper/6jfzg7tv2vjqg.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:47Z",
      "native_id": "10.3390/batteries12100415",
      "source": "crossref",
      "url": "https://www.mdpi.com/2313-0105/12/10/415"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "issn:2313-0105",
      "subfield": "electrochemistry-energy"
    }
  ],
  "title": "Cell-Wise Fault Warning for Lithium-Ion Battery Packs Using Local Outlier Factor and Validity-Gated Extreme-Value Thresholds",
  "title_text": "Cell-Wise Fault Warning for Lithium-Ion Battery Packs Using Local Outlier Factor and Validity-Gated Extreme-Value Thresholds",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:47Z",
  "url": "https://research.draconitic.com/paper/6jfzg7tv2vjqg",
  "venue": "Batteries",
  "versions": []
}