Note
Go to the end to download the full example code.
Maxwell 3D: Transformer#
This example shows how you can use PyAEDT to set core loss given a set of Power-Volume [kw/m^3] curves at different frequencies.
Perform required imports#
Perform required imports.
from pyaedt import downloads
from pyaedt import generate_unique_folder_name
from pyaedt import Maxwell3d
from pyaedt.generic.constants import unit_converter
from pyaedt.generic.general_methods import read_csv_pandas
Set AEDT version#
Set AEDT version.
aedt_version = "2024.1"
Download .aedt file example#
Set local temporary folder to export the .aedt file to.
temp_folder = generate_unique_folder_name()
aedt_file = downloads.download_file("core_loss_transformer", "Ex2-PlanarTransformer_2023R2.aedtz", temp_folder)
freq_curve_csv_25kHz = downloads.download_file("core_loss_transformer", "mf3_25kHz.csv", temp_folder)
freq_curve_csv_100kHz = downloads.download_file("core_loss_transformer", "mf3_100kHz.csv", temp_folder)
freq_curve_csv_200kHz = downloads.download_file("core_loss_transformer", "mf3_200kHz.csv", temp_folder)
freq_curve_csv_400kHz = downloads.download_file("core_loss_transformer", "mf3_400kHz.csv", temp_folder)
freq_curve_csv_700kHz = downloads.download_file("core_loss_transformer", "mf3_700kHz.csv", temp_folder)
freq_curve_csv_1MHz = downloads.download_file("core_loss_transformer", "mf3_1MHz.csv", temp_folder)
data = read_csv_pandas(filename=freq_curve_csv_25kHz)
curves_csv_25kHz = list(zip(data[data.columns[0]],
data[data.columns[1]]))
data = read_csv_pandas(filename=freq_curve_csv_100kHz)
curves_csv_100kHz = list(zip(data[data.columns[0]],
data[data.columns[1]]))
data = read_csv_pandas(filename=freq_curve_csv_200kHz)
curves_csv_200kHz = list(zip(data[data.columns[0]],
data[data.columns[1]]))
data = read_csv_pandas(filename=freq_curve_csv_400kHz)
curves_csv_400kHz = list(zip(data[data.columns[0]],
data[data.columns[1]]))
data = read_csv_pandas(filename=freq_curve_csv_700kHz)
curves_csv_700kHz = list(zip(data[data.columns[0]],
data[data.columns[1]]))
data = read_csv_pandas(filename=freq_curve_csv_1MHz)
curves_csv_1MHz = list(zip(data[data.columns[0]],
data[data.columns[1]]))
Launch AEDT#
Launch AEDT in graphical mode.
m3d = Maxwell3d(projectname=aedt_file,
designname="02_3D eddycurrent_CmXY_for_thermal",
specified_version=aedt_version,
new_desktop_session=True,
non_graphical=False)
C:\actions-runner\_work\_tool\Python\3.10.9\x64\lib\subprocess.py:1072: ResourceWarning: subprocess 12236 is still running
_warn("subprocess %s is still running" % self.pid,
C:\actions-runner\_work\pyaedt\pyaedt\.venv\lib\site-packages\pyaedt\generic\settings.py:383: ResourceWarning: unclosed file <_io.TextIOWrapper name='D:\\Temp\\pyaedt_ansys.log' mode='a' encoding='cp1252'>
self._logger = val
Set core loss at frequencies#
Create a new material, create a dictionary of Power-Volume [kw/m^3] points for a set of frequencies retrieved from datasheet provided by supplier and finally set Power-Ferrite core loss model.
mat = m3d.materials.add_material("newmat")
freq_25kHz = unit_converter(25, unit_system="Freq", input_units="kHz", output_units="Hz")
freq_100kHz = unit_converter(100, unit_system="Freq", input_units="kHz", output_units="Hz")
freq_200kHz = unit_converter(200, unit_system="Freq", input_units="kHz", output_units="Hz")
freq_400kHz = unit_converter(400, unit_system="Freq", input_units="kHz", output_units="Hz")
freq_700kHz = unit_converter(700, unit_system="Freq", input_units="kHz", output_units="Hz")
pv = {freq_25kHz: curves_csv_25kHz,
freq_100kHz: curves_csv_100kHz,
freq_200kHz: curves_csv_200kHz,
freq_400kHz: curves_csv_400kHz,
freq_700kHz: curves_csv_700kHz}
m3d.materials[mat.name].set_coreloss_at_frequency(points_list_at_freq=pv,
coefficient_setup="kw_per_cubic_meter",
core_loss_model_type="Power Ferrite")
coefficients = m3d.materials[mat.name].get_core_loss_coefficients(points_at_frequency=pv,
coefficient_setup="kw_per_cubic_meter")
Save project and close AEDT#
Save the project and close AEDT.
m3d.save_project()
m3d.release_desktop()
True
Total running time of the script: (0 minutes 47.615 seconds)