Samsung Sdi Co., Inc.

Postech Research and Business Development Foundation

Soohee Han

Minho Kim

Gyeonghwan Lee

Jang-Woo Lee

Jungsoo Kim

Huiyong Chun

Tae-Kyung Lee

A method of estimating a state of health of a battery, the method being performed by a computing apparatus, the method including: preparing a trained artificial neural network; generating input data by measuring at least one parameter of a battery; acquiring a plurality of output values each corresponding to a plurality of classes by inputting the input data into the trained artificial neural network; and generating a state of health estimation value of the battery using a plurality of preset health state sections each corresponding to the plurality of classes and the plurality of output values each corresponding to the plurality of classes.

Method and apparatus for estimating state of health of battery

A system and method of predicting variations in a capacity of a battery, the system including an ADFM management device including an experimental data collector to collect at least one first piece of data about the capacity of the battery, an ADF optimizer to optimize a first calculation equation, and a virtual data generator to generate at least one second piece of data; and a server including a training unit to train an artificial intelligence model for outputting the relative capacity variation value by using the at least one first piece of data and the at least one second piece of data as training data, and a prediction unit to obtain a relative capacity variation prediction value, which is output from the artificial intelligence model when the number of charge and discharge cycles and the charge and discharge conditions of the battery are input to the artificial intelligence model.

Battery capacity prediction system using charge and discharge cycles of a battery to predict capacity variations, and associated method

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Pohang-si, South Korea

Soohee Han