In generators, motors, and other similar electric machines, the electrical current that powers them produces magnetic fields that magnetize a number of the metallic components.
It is important to choose the right magnetic material for designing efficient machines, therefore, researchers at the Institute of Electrical Machines (IEM) at RWTH Aachen University in Germany analyzed current system for characterizing soft magnetic materials, which are magnetized easily. In order to find a better system for quality control, the researchers examined a number of factors that can influence the uncertainty intrinsic in the measurement of magnetic properties. Their findings are published this week in the AIP Advances journal, from AIP Publishing.
Low carbon steel is one example of a soft magnetic material that manufacturers use to make transformers, electric motors, and generators. In general, these materials serve the purpose of amplifying and guiding the magnetic flux when converting between electrical and mechanical energy in these machines. Magnetic measurements enable manufacturers to characterize those materials and to analyze how much power will be lost because of the magnetization process.
Manufacturing processes such as the cutting of the steel lamination influence the behavior of the soft magnetic material. Therefore such influence has to be measured and we must be able to model such parasitic effects.
Silas Elfgen, RWTH Aachen University
Although standardized methods are existing for evaluating magnetic properties, the researchers found them to be insufficient for applications such as designing traction drives in vehicles. These methods used one of the standard testing instruments, known as a single sheet tester, in order to characterize soft magnetic materials across different frequencies and magnetic flux densities.
The tests carried out by the researchers revealed that the existing parameters used to describe measurement qualities are inadequate for accurately evaluating uncertainties that occur at frequencies and magnetization levels of some applications that are currently of interest. The researchers also looked at other factors that affect the characterization and determined how much each parameter adds to the uncertainty. They suggest that these uncertainties can guide in selecting the most suitable soft magnetic material for a particular electrical machine.
These analyses can be used by everyone working with magnetic characteristics and magnetic model parameters. Further, it can be used in quality assurance of a product to define production features.