Abstract: The prevent invention relates a method and apparatus based on neural network for pre-diagnosing defect and fire in battery cell. A method based on neural network for pre-diagnosing defect and fire in battery cell in an apparatus for pre-diagnosing defect and fire in battery cell is proposed, the method including collecting, by the battery cell defect and fire pre-diagnosis apparatus, data including at least one of chemical composition, current, voltage, and temperature data measured for each predetermined time interval within each charge and discharge cycle while charging and discharging a plurality of batteries; training, by the battery to cell defect and fire pre-diagnosis apparatus, the neural network by inputting the collected data to the neural network; and predicting, by the battery cell defect and fire pre-diagnosis apparatus, a battery deviated from a main cluster of the neural network as defective.

Abstract: The prevent invention relates a method and apparatus based on neural network for pre-diagnosing defect and fire in battery cell. A method based on neural network for pre-diagnosing defect and fire in battery cell in an apparatus for pre-diagnosing defect and fire in battery cell is proposed, the method including collecting, by the battery cell defect and fire pre-diagnosis apparatus, data including at least one of chemical composition, current, voltage, and temperature data measured for each predetermined time interval within each charge and discharge cycle while charging and discharging a plurality of batteries; training, by the battery to cell defect and fire pre-diagnosis apparatus, the neural network by inputting the collected data to the neural network; and predicting, by the battery cell defect and fire pre-diagnosis apparatus, a battery deviated from a main cluster of the neural network as defective.