Material Identification

Introduction

Please note that this Material Identification module - for the moment - is exclusively available on Windows machines.

How to run the Material Identification tool

In Flux Supervisor, at the bottom left part of the window, the button Material Identification allows the user to launch the provided tool dedicated to the parameter identification of a magnetic material model (either in the case of a B(H) property and of an a posteriori iron losses model).

Please remark that the Material Identification module requires the Altair Compose^TM environment to be executed. Consequently, the user must install both Altair Flux^TM and Altair Compose^TM on his computer to perform a material identification with this tool. Both programs are available for download at Altair One.

Once the applications are linked, clicking on the Material Identification button should launch both Compose and the identification tool in Altair Compose's own environment, as shown in the Figure 1 below. The Flux Material Identification main panel will then invite the user to choose which kind of B(H) magnetic property or iron losses model identification he wants to perform.

Figure 1. Flux Material Identification panel after a successful startup.

Using the Material Identification tool

For most of the materials models in the Flux Material Identification tool, the identification consists of a 3-step procedure. The general workflow is described below:

• Step 1: After choosing a specific type of B(H) magnetic property or an iron losses model, the Flux Material Identification tool will ask the user for a file containing magnetic measurements representing the behavior of the material subjected to identification. The input data required by the Flux Material Identification tool is given by a .csv or a .xlsx file containing magnetic measurements. The file content and format depend on the specific kind of model being identified, as detailed in the next section.
• Step 2: Once the file is correctly loaded, the identification algorithm launches automatically and finds the best model parameter set fitting the selected model. The results are displayed automatically in the graph window, as shown in Figure 2 below. The red lines represent the reconstructed behavior provided by the identified model, while the blue lines correspond to the source measurement file. Depending on the model, the user may consider adjusting the parameters iteratively with the sliders on the left side of the panel.

  
  

  

  
  Figure 2. B(H) curves displayed using the analytic saturation + knee adjustment (arctg, 3 coef) model. In red , the fitted B(H), with the identified parameters appearing on the left side of the panel. The source B(H) measurements are shown in blue.

• Step 3: Another feature of this panel is the possibility to export the pyFlux command containing the identified model parameters of the material under identification. This export is achieved by clicking on the button Save pyFlux. The pyFlux command will be directly printed in the Compose console and may be copied and pasted in Flux's console, leading to an automatic creation of the material in a Flux project. This action also creates a python file containing the pyFlux command in a directory directly chooses by the user. With the help of this file, the material may be alternatively created in a Flux project by clicking on : Project > Command file > Run a python file.

Specificities of the identification models

In the previous section, a general workflow for the utilization of the Material Identification tool was presented. However, since the B(H) properties and iron losses models addressed by the tool are all different, specific remarks apply for each identification case.

For the Non-linear magnet described by Hc and Br module model, the input file must contain the magnet's B(H) curve (2nd and 3rd quadrants) and be provided either in .csv or a .xlsx formats. Two columns are required in the file: the first for the magnetic field H in amperes per meter and the second for the magnetic flux density B in teslas. An example input file is available here.

In the case of the Isotropic analytic saturation + knee adjustment (arctg, 3 coef) model, the input file containing B(H) data has the same file format described in the previous paragraph, but represents instead the anhysteretic curve or the first magnetization curve of the material. An example input file is available here.

For the hysteretic B(H) properties Isotropic hysteretic, Jiles-Atherton model; Isotropic hysteretic, Preisach model described by 4 parameters of a typical cycle; and the Isotropic hysteretic, Preisach model identified by N triplets, the required file must describe a complete B(H) hysteresis loop . The formats of the .csv or .xlsx file remain similar to the others mentioned above. An example file is provided here.

In the case of the LS model, the Material Identification tool will launch a dedicated tool called MILS, with its specific identification workflow. To perform an LS model identification with MILS, please refer to this documentation chapter.

In the case of the Modified Bertotti model, the input data required by the identification tool consists of a set of files either in .csv or .xlsx formats relating the peak magnetic flux density (in teslas) in the material to the specific iron losses (in W/kg). The input file also contains additional information such as frequency f (in Hz), material density ρ (in kg/m³), electrical conductivity σ (in S/m) and lamination thickness d (in m). An example input file is provided here. The goal of this identification tool is to find coefficients (k₁, k₂, k₃) that best fit the input data. By default, the exponents (α₁, α₂, α₃) are respectively forced to this set of value: (2 , 2 , 1.5) but they may be manually adjusted with the help of sliders.