EURO ASIA 8th. INTERNATIONAL CONGRESS ON APPLIED SCIENCES, Toskent, Uzbekistan, 15 - 16 March 2021, pp.114-115
CRITICAL MAGNETIC MATERIALS USING IN TRANSFORMER CORES OF AEROSPACE INDUSTRY
Prof. Dr. Dr. Naim DEREBAŞI
Physics Department, Bursa Uludag University, Gorukle Bursa, 16059, Turkey
Power loss, permeability, remenance, coercivity and weight of magnetic cores are becoming important criteria for economy, efficiency and performance consideration for design of power conversation equipment in aerospace industry. Performance requirements vary widely in traditional and emerging materials. This choice is often made more difficult because of a lack of suitable comparative magnetic data measured under different magnetising frequency conditions.
Grain oriented 3% SiFe is traditionally used widely, however recent competing materials such as amorphous and nanocrystalline with improved magnetic properties are being produced. The combination of high permeability and low core loss of amorphous ribbon materials make them suitable for wound cores applications. The lack of crystalline structure in the atomic structure of amorphous alloys produces advantages over existing magnetic materials. The superior magnetic and .mechanical properties as well as their low cost have attracted to use them in many industrial application and various types of sensors and transducers.
Nanocrystalline materials are mostly used for medium to high frequency applications because of their higher magnetic permeability and high operating flux density and small sizes.
In this research direct comparison of ac properties of toroidal cores made from wound grain oriented 3%SiFe, amorphous and nano-crystalline strip materials was investigated. Measurements on toroidal cores were carried out using a system comprising a magnetisation circuit including a signal waveform source, an amplifier and a matching transformer and two high precision multimeters in order to monitor the primary current and secondary induced voltage.
Recently, artificial neural networks have successfully been used for the prediction of magnetic performance in electromagnetic devices made from soft magnetic materials. In these materials, flux density distribution must be known for power loss calculation, material selection and core design. It is possible to calculate them under some assumptions; however, it is difficult to measure them experimentally. Artificial neural network and MATLAB® Curve Fitting ToolboxTM are used to analyse data obtained from measurements in prediction and calculation of magnetic properties of toroidal cores. Prediction of magnetic performance with improving model and a simple analytical equation giving accurate results as depending on experimental results for each core tested made of different material have been determined. The results obtained from improving ANN model and analytical equations are in good agreement with experimental results.
Key words: electrical steels, amorphous and nanocrystalline materials, artificial neural networks,