{
  "abstract": "A critical design blind spot persists in contemporary electric vehicle (EV) safety engineering: ISO 26262 functional-safety frameworks generally treat battery State-of-Health (SoH) as a passive maintenance metric rather than a live, mode-governing safety variable. This paper proposes a five-layer theoretical co-design framework that integrates SoH estimation, power-margin monitoring, functional-safety decision logic, actuation, and lifecycle management. A qualitative Fault Tree Analysis and preliminary Hazard Analysis and Risk Assessment are used to examine the representative BMS–ADAS power-interface hazard. The electrical analysis introduces a bounded DC/DC converter model and distinguishes two explicit converter-control scenarios: regulated operation with no active hard limit and an adverse 5.15 A hard-input-current-limit boundary condition. For the stated 851 W transient load, both scenarios retain positive converter margin; failed shedding of a 551 W comfort load is therefore the dominant source of power-margin compression, while the isolated SoH contribution is 0 W under regulated operation and approximately 40 W under the adverse hard-limit condition. A separate illustrative LiDAR subsystem-allocation model yields a beta-derived additional stopping-distance estimate of approximately 0.84–1.40 m, while an independently defined 100 ms recovery-delay scenario yields 1.67 m. These estimates are analytical scenario results rather than device-validated predictions. Platform-specific converter, power-allocation, sensor, timing, and hardware-in-the-loop validation is identified as the essential next steps.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Legal Medicine, Shiga University of Medical Science",
    "Faculty of Artificial Intelligence and Engineering, Multimedia University",
    "Department of Computer Science, College of Computing and Information Technology, Shaqra University",
    "Department of Electrical, Electronic and Communication Engineering, Military Institute of Science and Technology (MIST)",
    "Department of Computer Science and Engineering, Military Institute of Science and Technology"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Nick Barua"
    },
    {
      "affs": [
        1
      ],
      "name": "Md Tanjil Sarker"
    },
    {
      "affs": [
        2
      ],
      "name": "Marran Al Qwaid"
    },
    {
      "affs": [
        1
      ],
      "name": "Md. Shabiul Islam"
    },
    {
      "affs": [
        3
      ],
      "name": "Shah Mohazzem Hossain"
    },
    {
      "affs": [
        4
      ],
      "name": "Kazy Noor-e-Alam Siddiquee"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/760dwpaw6eq5f.bib",
  "cited_by": 1,
  "doi": "10.1038/s41598-026-65007-4",
  "fulltext_url": "https://doi.org/10.1038/s41598-026-65007-4",
  "id": "760dwpaw6eq5f",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://doi.org/10.1038/s41598-026-65007-4",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "Q"
    ],
    [
      "lcc",
      "R"
    ],
    [
      "openalex",
      "2213|Safety Systems Engineering in Autonomy"
    ]
  ],
  "openalex": "W7172326596",
  "pdf_url": "https://www.nature.com/articles/s41598-026-65007-4_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-08-01",
  "publisher": "Nature Portfolio",
  "ris": "https://research.draconitic.com/paper/760dwpaw6eq5f.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:45:59Z",
      "native_id": "f500eebdca8c4c0b855ac2cf682b0e2f",
      "source": "doaj",
      "url": "https://doi.org/10.1038/s41598-026-65007-4"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "lcc:R",
      "subfield": "general"
    }
  ],
  "title": "Battery state-of-health as a functional safety variable: an ISO 26262-aligned AI framework for electric vehicle ADAS power integrity",
  "title_text": "Battery state-of-health as a functional safety variable: an ISO 26262-aligned AI framework for electric vehicle ADAS power integrity",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:45:59Z",
  "url": "https://research.draconitic.com/paper/760dwpaw6eq5f",
  "venue": "Scientific Reports",
  "versions": []
}