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Fujitsu Develops Design Technology Using AI for Magnetic Material Geometries


Fujitsu Laboratories Ltd. and Fujitsu Limited announced the development of technology that can automate the design of magnetic material geometries, using AI to minimize energy loss. To design magnetic materials, which are common components in electronic devices, developers previously worked under conditions where they had to spend large amounts of time and money conducting tests based on trial and error. The new technology automates and digitizes the development of prototypes, significantly improving R&D efficiency. In addition, this technology is expected to enable geometric designs for magnets, even without specialized expertise, in a variety of R&D fields, such as power electronics and electric vehicle motors. Fujitsu aims to make design services incorporating this technology available through the cloud in 2020.

Development Background

Magnetic materials, which become magnets when a magnetic field is applied, are used in a variety of components and devices, including electric vehicle motors and inductors, which store electrical energy in the power sources of electronic devices. However, there will always be some magnetic loss, where a portion of energy is lost as heat, due to magnetism. This magnetic loss can change significantly based on the geometry of the magnetic materials, and is directly linked with the energy efficiency of the component or device. Therefore, in order to deliver high energy efficiency, it has become important to design the geometries of magnetic materials with consideration for magnetic loss.


With existing design methods for the geometries of magnetic materials, because of the strong non-linearity unique to magnetic materials (magnetic hysteresis), it is difficult to find an optimal geometry for minimizing magnetic loss, thereby making automated geometry design challenging. In addition, even when a completed design is simulated, there can be errors in the magnetic loss simulation that differ by several multiples or even several orders of magnitude from experimentally measured values, inhibiting the sufficient and accurate predictions for design development. As a result, magnetic material geometry designs had to rely on the experience and insight of designers as well as experimental trial and error, requiring substantial expenses of time and money.

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