{
  "$type": "site.standard.document",
  "description": "The present invention relates to a battery cell defectiveness and fire early diagnosis method and apparatus based on a neural network. A method for performing early diagnosis of battery cell defectiveness and fire through neural network-based self-supervised learning by a battery cell defectiveness…",
  "path": "/patents/1399209",
  "publishedAt": "2026-02-11T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "B60L3/0046",
    "KOREA POWER CELL CO LTD [KR]"
  ],
  "textContent": "The present invention relates to a battery cell defectiveness and fire early diagnosis method and apparatus based on a neural network. A method for performing early diagnosis of battery cell defectiveness and fire through neural network-based self-supervised learning by a battery cell defectiveness and fire early diagnosis apparatus for predicting battery cell defectiveness comprises the steps in which the battery cell defectiveness and fire early diagnosis apparatus: collects data including at least one of chemical composition, current, voltage, or temperature data measured at predetermined time intervals within each charge/discharge cycle while charging and discharging a plurality of batteries; inputs the collected data to the neural network to train the neural network; and predicts a battery deviating from a main cluster of the neural network as being defective.",
  "title": "BATTERY CELL DEFECTIVENESS AND FIRE EARLY DIAGNOSIS METHOD AND APPARATUS BASED ON NEURAL NETWORK"
}