Samsung Sdi Co., Inc.

Postech Research and Business Development Foundation

Union Materials Corporation

Minho Kim

Soohee Han

Gyeonghwan Lee

Dongyoung Lee

Kilsoo Park

Eunseon Cheong

Jung-Whan Lee

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

A ferrite magnetic material comprising a primary phase of a magnetoplumbite-type hexagonal ferrite, the primary phase having a composition represented by formula (I), can provide improved magnetic properties in terms of the residual magnetic flux density (Br), intrinsic coercive force (iHc), squareness (Hk/iHc), and maximum energy product (B.Hmax). Therefore, a segment-type permanent magnet derived therefrom can be used in the manufacture of small type motors for automobiles, motors for electric equipments as well as for home appliances, and other devices.

Magnetoplumbite-type ferrite magnetic material and segment-type permanent magnet derived therefrom

Growing community of inventors

Pohang-si, South Korea

Minho Kim