{
  "abstract": "Effective thermal management is essential for ensuring the safety, performance, and longevity of Lithium-ion batteries (LIBs). In this study, an optimized hybrid Battery Thermal Regulation System (BTRS) is proposed, integrating helical liquid cooling mini-channels and phase change material (PCM) embedded in a copper foam matrix (CPCM) to enhance heat dissipation. To efficiently explore the complex design space, a coupled framework integrating numerical simulations, a Genetic Algorithm (GA), and Artificial Neural Networks (ANN) was developed. The approach successfully identified an ideal configuration (OCD1) characterized by a 10 mm PCM thickness, a 0.08 m/s inlet velocity, and a $$65^\\circ $$ helical angle. Under a severe 3C discharge condition, this optimal design achieved a maximum temperature reduction of 21.27 K, representing an 82.25% improvement over a standalone cell. Furthermore, the optimized hybrid system demonstrated superior cooling efficacy compared to individual strategies, outperforming case A (liquid cooling) by 33.67%, case B (pure PCM) by 69.35%, and case C (CPCM) by 45%. The developed ANN model exhibited high predictive accuracy, with R2 values exceeding 0.99 for both thermal responses. These findings provide a high fidelity and scalable framework for advanced thermal management of next-generation electric vehicle battery systems.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "Sonia Naghizadeh Mahjoub"
    },
    {
      "name": "Mohammad Vajdi",
      "orcid": "0000-0003-4559-1134"
    },
    {
      "name": "Kourosh Vaferi",
      "orcid": "0000-0002-2884-7049"
    },
    {
      "name": "Farhad Sadegh Moghanlou"
    },
    {
      "name": "Ebrahim Abdi Aghdam"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ezypn93br4gqz.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-75647-1",
  "fulltext_url": "https://doi.org/10.1038/s41598-026-75647-1",
  "id": "ezypn93br4gqz",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://www.nature.com/articles/s41598-026-75647-1",
  "language": "en",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "Q"
    ],
    [
      "lcc",
      "R"
    ],
    [
      "openalex",
      "2203|Advanced Battery Technologies Research"
    ]
  ],
  "openalex": "W7221818564",
  "pdf_url": "https://www.nature.com/articles/s41598-026-75647-1.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-14",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/ezypn93br4gqz.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:28Z",
      "native_id": "10.1038/s41598-026-75647-1",
      "source": "crossref",
      "url": "https://www.nature.com/articles/s41598-026-75647-1"
    },
    {
      "first_seen": "2026-10-30T13:45:57Z",
      "native_id": "911f3f8f21404fef963c7401da7a2043",
      "source": "doaj",
      "url": "https://doi.org/10.1038/s41598-026-75647-1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "lcc:R",
      "subfield": "general"
    }
  ],
  "title": "ANN-GA-based optimization of a hybrid battery thermal regulation system with helical liquid cooling, PCM, and copper foam",
  "title_text": "ANN-GA-based optimization of a hybrid battery thermal regulation system with helical liquid cooling, PCM, and copper foam",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:45:57Z",
  "url": "https://research.draconitic.com/paper/ezypn93br4gqz",
  "venue": "Scientific Reports",
  "versions": []
}