1 Material database for power electronic usage

The main purpose of the material database is to provide various materials for FEM simulations or other calculations in which material data from data sheets or own measurements are required.

Possible application scenarios:

  • FEM Magnetics Toolbox (FEMMT) loads the permeability or the conductivity of the core from the database, depending on the material.

  • Graphical user interface (GUI) in FEMMT can compare properties of the material stored in material database.

1.1 Overview features

1.1.1 Usable features

  • Human-readable database based on a .json-file

  • Input features:
    • Write magnetic parameters into the database

      • Amplitude of permeability

      • Angle of permeability

      • Power loss density (hysteresis losses)

      • Magnetic flux density

      • Magnetic field strength

    • Write electric parameters into the database

      • Amplitude of permittivity

      • Angle of permittivity

      • Power loss density (eddy current losses)

      • Electric flux density

      • Electric field strength

    • Write datasheet data into the database

  • Output features:

    • Get the magnetic parameters from the database

    • Providing permeability and permittivity data for FEMMT

  • Interpolation of material data (both electric and magnetic parameters)

  • GUI features (included in FEMMT):

    • Compare the datasheet values of different ferrite cores (e.g. BH-curves or power-loss curves)

    • Materials for comparison:

      • N95

      • N87

      • N49

      • PC200

      • DMR96A

1.1.2 Planned features (Roadmap for 202x)

  • Input features:

    • Universal function to write data into the database

  • Output features:

    • Get the electric parameters from the database

    • Extract data from the database as a specific data file (e.g. .csv)

  • Plotting features:

    • Plot the data of a specific ferrite material, e.g. the amplitude of the permeability over the magnetic flux density

  • Filter features:

    • Get all available data for specific filter keys (e.g. temperature, frequency, material etc.)

    • Filter for some specific value intervals (e.g. 10mT < B-flux < 30mT)

1.2 Installation

pip install materialdatabase

1.3 Basic usage and minimal example

Material properties:

material_db = mdb.MaterialDatabase()
materials = material_db.material_list_in_database()
initial_u_r_abs = material_db.get_material_property(material_name="N95", property="initial_permeability")
core_material_resistivity = material_db.get_material_property(material_name="N95", property="resistivity")
_images/database_json.png

Interpolated permeability and permittivity data of a Material:

b_ref, mu_r_real, mu_r_imag = material_db.permeability_data_to_pro_file(temperature=25, frequency=150000, material_name = "N95", datatype = "complex_permeability",
                                      datasource = mdb.MaterialDataSource.ManufacturerDatasheet, parent_directory = "")

epsilon_r, epsilon_phi_deg = material_db.get_permittivity(temperature= 25, frequency=150000, material_name = "N95", datasource = "measurements",
                                      datatype = mdb.MeasurementDataType.ComplexPermittivity, measurement_setup = "LEA_LK",interpolation_type = "linear")

These function return complex permittivity and permeability for a certain operation point defined by temperature and frequency.

1.4 GUI (FEMMT)

The materials in database can be compared with help GUI in FEM magnetics toolbox. In database tab of GUI, the loss graphs and B-H curves from the datasheets of up to 5 materials can be compared.

FEMMT can be installed using the python pip package manager.

pip install femmt

For working with the latest version, refer to the documentation

gui_database

gui_database_loss

1.5 Bug Reports

Please use the issues report button within github to report bugs.

1.6 Changelog

Find the changelog here.

2 Materialdatabase function documentation

Functions of the material database.

materialdatabase.material_data_base_functions.calc_electric_field_strength_from_lecroy_voltage_data(voltage: ndarray | list, height: float = 1.0)

Calculate the electric field strength based on the voltage data of a lecroy oscilloscope.

Parameters:

  • voltage (list or ndarray) – array-like of the voltage in V

  • height (float) – height of probe in m

Returns:

array of electric field strength values

materialdatabase.material_data_base_functions.calc_electric_flux_density_based_on_current_array_and_frequency(current: ndarray | list, frequency: float = 1.0, cross_section: float = 1.0)

Calculate the electric flux density based on the current and the frequency.

Parameters:

  • current (ndarray or list) – array-like of the current in A

  • frequency (float) – frequency value in Hz

  • cross_section (float) – cross-section of probe in m^2

Returns:

arrray of electric flux density values

materialdatabase.material_data_base_functions.calc_electric_flux_density_based_on_current_array_and_time_array(current_array: ndarray | list, time: ndarray | list, cross_section: float = 1.0)

Calculate the electric flux density based on the current data of a lecroy oscilloscope.

Parameters:

  • current_array (ndarray or list) – array-like of the current in A

  • time (ndarray or list) – array of time values of measurement in s

  • cross_section (float) – cross-section of probe in m^2

Returns:

array of electric flux density values

materialdatabase.material_data_base_functions.calc_magnetic_field_strength_based_on_current_array(current: ndarray | list, primary_winding: int = 1, l_mag: float = 1.0)

Calculate the magnetic field strength based on the current.

Parameters:

  • current (ndarray or list) – array-like of the current in A

  • primary_winding (int) – number of primary windings

  • l_mag (float) – mean magnetic path length in m

Returns:

array with magnetic field strength curve in A/m

materialdatabase.material_data_base_functions.calc_magnetic_flux_density_based_on_voltage_array_and_frequency(voltage: ndarray | list, frequency: float = 1.0, secondary_winding: int = 1, cross_section: float = 1.0)

Calculate the magnetic flux density based on the voltage and the frequency.

ASSUMPTION: EXACTLY ONE PERIOD! Based on the length of the voltage array and the frequency the time-array is constructed for the integration.

Parameters:

  • voltage (ndarray or list) – array-like of the voltage in V

  • frequency (float) – frequency value in Hz

  • secondary_winding (int) – number of secondary windings

  • cross_section (float) – value of the cross-section of the core in m^2

Returns:

array with magnetic flux density curve in T

materialdatabase.material_data_base_functions.calc_magnetic_flux_density_based_on_voltage_array_and_time_array(voltage: ndarray | list, time: ndarray | list, secondary_winding: int = 1, cross_section: float = 1)

Calculate the magnetic flux density based on the voltage and the time.

ASSUMPTION: EXACTLY ONE PERIOD!

Parameters:

  • voltage (ndarray or list) – array-like of the voltage in V

  • time (ndarray or list) – array-like of the time in s

  • secondary_winding (int) – number of secondary windings

  • cross_section (float) – value of the cross-section of the core in m^2

Returns:

array with magnetic flux density curve in T

materialdatabase.material_data_base_functions.calc_mu_r_from_b_and_h_array(b: ndarray | list, h: ndarray | list)

Calculate the amplitude of the relative permeability based on a magnetic flux density and a magnetic field strength array.

Parameters:

  • b (ndarray or list) – magnetic flux density array

  • h (ndarray or list) – magnetic field strength array

Returns:

amplitude of the relative permability

materialdatabase.material_data_base_functions.check_input_permeability_data(datasource: str, material_name: str, temperature: float, frequency: float) → None

Check input permeability data for correct input parameters.

  • datasource must be ‘measurements’ or ‘manufacturer_datasheet’

  • material_name, T, f must be different from None

Parameters:

  • datasource (str) – datasource as a string

  • material_name (str) – material name as a string

  • temperature (float) – temperature in °C

  • frequency (float) – frequency in Hz

materialdatabase.material_data_base_functions.clear_permeability_measurement_data_in_database(material_name: str, measurement_setup: str)

Clear the permeability data in the database given a material and measurement setup.

Parameters:

  • material_name (str) – name of the material

  • measurement_setup (str) – name of the measurement setup

materialdatabase.material_data_base_functions.clear_permittivity_measurement_data_in_database(material_name: str, measurement_setup: str)

Clear the permittivity data in the database for a specific material.

Parameters:

  • material_name (str) – name of material

  • measurement_setup (str) – name of measurement setup

materialdatabase.material_data_base_functions.create_empty_material(material_name: str, manufacturer: str, initial_permeability: float, resistivity: float, max_flux_density: float, volumetric_mass_density: float)

Create an empty material slot in the database.

Parameters:

  • material_name (str) – name of the material

  • manufacturer (str) – name of the manufacturer

  • initial_permeability (float) – value of the initial permeability

  • resistivity (float) – value of the resistivity

  • max_flux_density (float) – saturation value of the magnetic flux density

  • volumetric_mass_density (float) – value of the volumetric mass density

materialdatabase.material_data_base_functions.create_permeability_file_name_lea_lk(quantity: str = 'p_hys', frequency: float = 100000, material_name: str = 'N49', temperature: float = 30)

Create the file name for permeability data of LEA_LK.

Parameters:

  • quantity (str) – measured quantiy (e.g. p_hys)

  • material_name (str) – name of the material

  • frequency (float) – frequency value in Hz

  • temperature (float) – temperature value in °C

Returns:

correct file name for LEA_LK

materialdatabase.material_data_base_functions.create_permeability_measurement_in_database(material_name: str, measurement_setup: str, company: str = '', date: str = '', test_setup_name: str = '', toroid_dimensions: str = '', measurement_method: str = '', equipment_names: str = '', comment: str = '')

Create a new permeability section in the database for a material.

Parameters:

  • material_name (str) – name of the material

  • measurement_setup (str) – name of the measurement setup

  • company (str) – name of the company

  • date (str) – date of measurement

  • test_setup_name (str) – information of the test setup

  • toroid_dimensions (str) – dimensions of the probe

  • measurement_method (str) – name of the measurement method

  • equipment_names (str) – name of the measurement equipment

  • comment (str) – comment regarding the measurement

materialdatabase.material_data_base_functions.create_permeability_neighbourhood_datasheet(temperature: float, frequency: float, list_of_permeability_dicts: ndarray | list)

Create a neighbourhood for permeability data of a datasheet.

Parameters:

  • temperature (float) – temperature value in °C

  • frequency (float) – frequency value in Hz

  • list_of_permeability_dicts (ndarray or list) – list of permeability data dicts

Returns:

neighbourhood

materialdatabase.material_data_base_functions.create_permeability_neighbourhood_measurement(temperature: float, frequency: float, list_of_permeability_dicts: ndarray | list)

Create a neighbourhood for permeability data of a measurement.

Parameters:

  • temperature (float) – temperature value in °C

  • frequency (float) – frequency value in Hz

  • list_of_permeability_dicts (ndarray or list) – list of permeability dicts

Returns:

neighbourhood

materialdatabase.material_data_base_functions.create_permittivity_file_name_lea_lk(quantity: str = 'p_hys', frequency: float = 100000, material_name: str = 'N49', temperature: float = 30)

Create the file name for permittivity data of LEA_LK.

Parameters:

  • quantity (str) – measured quantiy (e.g. p_hys)

  • frequency (float) – frequency value in Hz

  • material_name (str) – name of the material

  • temperature (float) – temperature value in °C

Returns:

correct file name for LEA_LK

materialdatabase.material_data_base_functions.create_permittivity_measurement_in_database(material_name: str, measurement_setup: str, company: str = '', date: str = '', test_setup_name: str = '', probe_dimensions: str = '', measurement_method: str = '', equipment_names: str = '', comment: str = '')

Create a new permittvity section in the database for a material.

Parameters:

  • material_name (str) – name of the material

  • measurement_setup – name of the measurement setup

  • company (str) – name of the company

  • date (str) – date of measurement

  • test_setup_name (str) – information of the test setup

  • probe_dimensions (str) – dimensions of the probe

  • measurement_method (str) – name of the measurement method

  • equipment_names (str) – name of the measurement equipment

  • comment (str) – comment regarding the measurement

materialdatabase.material_data_base_functions.create_permittivity_neighbourhood(temperature: float, frequency: float, list_of_permittivity_dicts: ndarray | list)

Create neighbourhood for permittivity data.

Parameters:

  • temperature (float) – temperature value in °C

  • frequency (float) – frequency value in Hz

  • list_of_permittivity_dicts (ndarray or list) – list of permittivity data dicts

Returns:

neighbourhood

materialdatabase.material_data_base_functions.create_steinmetz_neighbourhood(temperature: float, list_of_steinmetz_dicts: ndarray | list)

Create neighbourhood for steinmetz data.

Parameters:

  • temperature (float) – temperature value in °C

  • list_of_steinmetz_dicts (ndarray or list) – list of steinmetz data dicts

Returns:

neighbourhood

materialdatabase.material_data_base_functions.crop_3_with_1(x: ndarray | list, y: ndarray | list, z: ndarray | list, xa: int | float, xb: int | float)

Crop three arrays based on one array.

Parameters:

  • x (ndarray or list) – array crop is based on

  • y (ndarray or list) – first array to get cropped

  • z (ndarray or list) – second array to get cropped

  • xa (float or int) – start value of crop

  • xb (float or int) – end value of crop

Returns:

the three cropped arrays

materialdatabase.material_data_base_functions.crop_data_fixed(x: list, pre_cropped_values: int = 0, post_cropped_values: int = 0)

Crop an array based on the given indices.

IMPORTANT! THE SECOND INDEX IS COUNTED BACKWARDS(NEGATIVE)!

Parameters:

  • x (list) – array to get cropped

  • pre_cropped_values (int) – start value

  • post_cropped_values (int) – end value, but counted backwards

Returns:

cropped data

materialdatabase.material_data_base_functions.eps_phi_deg__from_eps_r_and_p_eddy(frequency: ndarray | float, e_peak: ndarray | float, eps_r: ndarray | float, p_eddy: ndarray | float)

Calculate the angle of the permittivity.

Parameters:

  • frequency (ndarray or float) – frequency

  • e_peak (ndarray or float) – peak value of the electric field strength

  • eps_r (ndarray or float) – peak value of the amplitude of the permittivity

  • p_eddy (ndarray or float) – eddy current loss density

Returns:

angle of permittivity in degree

materialdatabase.material_data_base_functions.export_data(parent_directory: str = '', file_format: str | None = None, b_ref_vec: ndarray | list | None = None, mu_r_real_vec: ndarray | list | None = None, mu_r_imag_vec: ndarray | list | None = None, silent: bool = False)

Export data from the material database in a certain file format.

Parameters:

  • parent_directory (str) – path to parent directory

  • file_format (str) – export format, e.g. ‘pro’ to export a .pro-file

  • b_ref_vec (ndarray or list) – reference vector for mu_r_real and mu_r_imag

  • mu_r_real_vec (ndarray or list) – real part of mu_r_abs as a vector

  • mu_r_imag_vec (ndarray or list) – imaginary part of mu_r_abs as a vector

  • silent (bool) – enables/disables print

materialdatabase.material_data_base_functions.find_nearest(array: ndarray | list, value: float)

Find the nearest value in an array.

Parameters:

  • array (ndarray or list) – array to search

  • value (float) – desired value

Returns:

two values of the array with the wanted value in between

materialdatabase.material_data_base_functions.find_nearest_frequencies(permeability: ndarray | list, frequency: float)

Find the nearest frequency value for permeability data.

Parameters:

  • permeability (ndarray or list) – permeability data

  • frequency (float) – desired frequency value in Hz

Returns:

two frequency values in Hz with the desired value in between

materialdatabase.material_data_base_functions.find_nearest_neighbour_values_permeability(permeability_data: ndarray | list, temperature: float, frequency: float)

Find the nearest temperature and frequency values for a given neighbourhood of permeability data.

Parameters:

  • permeability_data (ndarray or list) – permeability data

  • temperature (float) – temperature value in °C

  • frequency (float) – frequency value in Hz

Returns:

lower temperature value in °C, higher temperature value in °C, lower frequency value in Hz, higher frequency value in Hz

materialdatabase.material_data_base_functions.find_nearest_neighbours(value: float, list_to_search_in: ndarray | list)

Return the two values with the wanted value in between and additional the indices of the corresponding values.

Only works for sorted lists (small to big).

Case 0: if len(list_to_search_in) == 1: return duplicated Case 1: if value == any(list_to_search_in): return duplicated Case 2: if value inbetween: return neighbours Case 3a: value smaller than data: return smallest two Case 3b: if value is bigger than data: return biggest two

Parameters:

  • value (float) – desired value

  • list_to_search_in (ndarray or list) – array to search for value

Returns:

lower index, lower value, higher index, higher value

materialdatabase.material_data_base_functions.find_nearest_temperatures(permeability: ndarray | list, f_l: float, f_h: float, temperature: float)

Find the nearest temperature value between two frequency points.

Parameters:

  • permeability (ndarray or list) – permeability data

  • f_l (float) – lower frequency value in Hz

  • f_h (float) – higher frequency value in Hz

  • temperature (float) – desired temperature value in °C

Returns:

two temperature values in °C with the desired value in between

materialdatabase.material_data_base_functions.get_all_frequencies_for_material(material_path: str)

Get all the frequency values for a given material.

Parameters:

material_path (str) – path to the material

Returns:

all frequency values in Hz of the given material

materialdatabase.material_data_base_functions.get_all_temperatures_for_directory(toroid_path: str)

Get all the temperature values for a given toroid probe.

Parameters:

toroid_path (str) – path of the toroid probe

Returns:

all temperature values in °C of the specific toroid probe

materialdatabase.material_data_base_functions.get_bh_integral_shoelace(b: ndarray, h: ndarray, f: float)

Calculate the hysteresis loss density.

Parameters:

  • b (ndarray) – magnetic flux density in T

  • h (ndarray) – magnetic field strength in A/m

  • f (float) – frequency in Hz

Returns:

hysteresis loss density in W/m^3

materialdatabase.material_data_base_functions.get_bh_integral_trapezoid(b: ndarray, h: ndarray, f: float)

Calculate the hysteresis loss density.

Parameters:

  • b (ndarray) – magnetic flux density in T

  • h (ndarray) – magnetic field strength in A/m

  • f (float) – frequency in Hz

Returns:

hysteresis loss density in W/m^3

materialdatabase.material_data_base_functions.get_permeability_data_from_lea_lk(location: str, frequency: float, temperature: float, material_name: str, no_interpolation_values: int = 20)

Get the permeability data from LEA_LK.

Parameters:

  • location (str) – location of the permeability data

  • frequency (float) – frequency value in Hz

  • temperature (float) – temperature value in °C

  • material_name (str) – name of the material

  • no_interpolation_values (int) – number of interpolation values

Returns:

magnetic flux density, amplitude of the permeability, angle of the permeability

materialdatabase.material_data_base_functions.get_permeability_data_from_lea_mtb(location: str)

Get the permeability data from the material test bench.

Parameters:

location (str) – location of the permability data

Returns:

magnetic flux density, amplitude of the permeability, angle of the permeability

materialdatabase.material_data_base_functions.get_permeability_property_from_lea_lk(path_to_parent_folder: str, quantity: str, frequency: float, material_name: str, temperature: float, sub_folder_name: str = 'Core_Loss')

Get the proberty of the permeability from LEA_LK.

Parameters:

  • path_to_parent_folder (str) – path to permeability data

  • quantity (str) – name of the measured quantity

  • material_name (str) – name of the material

  • frequency (float) – frequency value in Hz

  • temperature (float) – temperature value in °C

  • sub_folder_name (str) – name of the sub folder

Returns:

amplitude of the permeability, angle of the permeability

materialdatabase.material_data_base_functions.get_permeability_property_from_lea_mtb(path_to_parent_folder: str)

Get the proberty of the permeability from the material test bench.

Parameters:

path_to_parent_folder (str) – path to permeability data

Returns:

magnetic flux density, amplitude of the permeability, angle of the permeability

materialdatabase.material_data_base_functions.get_permittivity_data_from_lea_lk(location: str, temperature: float, frequency: float, material_name: str)

Get the permittivity data from LEA_LK.

Parameters:

  • location (str) – location of the permittivity data

  • temperature (float) – temperature value

  • frequency (float) – frequency value in Hz

  • material_name (str) – name of the material

Returns:

amplitude of the permittivity, angle of the permittivity

materialdatabase.material_data_base_functions.get_permittivity_property_from_lea_lk(path_to_parent_folder: str, quantity: str, frequency: float, material_name: str, temperature: float, sub_folder_name: str = 'Core_Loss')

Get the proberty of the permittivity from LEA_LK.

Parameters:

  • path_to_parent_folder (str) – path to permittivity data:

  • quantity (str) – name of the measured quantity

  • frequency (float) – frequency value in Hz

  • material_name (str) – name of the material

  • temperature (float) – temperature value in °C

  • sub_folder_name (str) – name of the sub folder

Returns:

amplitude of the permittivity, angle of the permittivity

materialdatabase.material_data_base_functions.getdata_datasheet(permeability: ndarray | list, variable: float, frequency: float, temperature_1: float, temperature_2: float)

Interpolation of permeability data between two temperatures at a constant frequency.

Linear Interpolation between temperature_1 and temperature_2 to get a value for the temperature “variable”.

Parameters:

  • permeability (ndarray or list) – permeability data

  • variable (float) – desired temperature value in °C

  • frequency (float) – frequency value in Hz

  • temperature_1 (float) – first temperature value in °C

  • temperature_2 (float) – second temperature value in °C

Returns:

magnetic flux density, real part of permeability and imaginary part of permeability

materialdatabase.material_data_base_functions.getdata_measurements(permeability: ndarray | list, variable: float, frequency: float, temperature_1: float, temperature_2: float, b_t: ndarray | list)

Linear interpolation of the permeability data between two temperatures at a constant frequency.

Parameters:

  • permeability (ndarray or list) – permeability data

  • variable (float) – desired temperature variable in °C

  • frequency (float) – frequency value in Hz

  • temperature_1 (float) – temperature value under the desired value in °C

  • temperature_2 (float) – temperature value above the desired value in °C

  • b_t (ndarray or list) – magnetic flux density

Returns:

amplitude of the permeability, angle of the permeability

materialdatabase.material_data_base_functions.integrate(x_data: ndarray | list, y_data: ndarray | list)

Integrate the function y_data = f(x_data).

Parameters:

  • x_data (ndarray or list) – x-axis

  • y_data (ndarray or list) – y-axis

Returns:

defined integral of y_data

materialdatabase.material_data_base_functions.interpolate_a_b_c(a: ndarray | list, b: ndarray | list, c: ndarray | list, no_interpolation_values: int = 20)

Interpolation between three arrays based on the first array.

Parameters:

  • a (ndarray or list) – array that is the base of the interpolation

  • b (ndarray or list) – array that gets interpolated based on the values of array a

  • c (ndarray or list) – array that gets interpolated based on the values of array a

  • no_interpolation_values (int) – number of interpolation values

Returns:

the three interpolated arrays

materialdatabase.material_data_base_functions.interpolate_b_dependent_quantity_in_temperature_and_frequency(temperature: float, frequency: float, temperature_low: float, temperature_high: float, frequency_low: float, frequency_high: float, b_t_low_f_low: ndarray, f_b_T_low_f_low: ndarray, b_T_high_f_low: ndarray, f_b_T_high_f_low: ndarray, b_T_low_f_high: ndarray, f_b_T_low_f_high: ndarray, b_T_high_f_high: ndarray, f_b_T_high_f_high: ndarray, no_interpolation_values: int = 8, y_label: str | None = None, plot: bool = False)

Interpolate a magnet flux density dependent quantity in temperature and frequency.

Parameters:

  • temperature (float) – desired temperature in °C

  • frequency (float) – desired frequency in Hz

  • temperature_low (float) – lower temperature value in °C

  • temperature_high (float) – higher temperature value in °C

  • frequency_low (float) – lower frequency value in Hz

  • frequency_high (float) – higher frequency value in Hz

  • b_t_low_f_low (ndarray) – magnetic flux density at the lower temperature in °C and the lower frequency value in Hz

  • f_b_T_low_f_low (ndarray) – function dependent of b at the lower temperature in °C and the lower frequency value in Hz

  • b_T_high_f_low (ndarray) – magnetic flux density at the higher temperature in °C and the lower frequency value in Hz

  • f_b_T_high_f_low (ndarray) – function dependent of b at the higher temperature in °C and the lower frequency value in Hz

  • b_T_low_f_high (ndarray) – magnetic flux density at the lower temperature in °C and the higher frequency value in Hz

  • f_b_T_low_f_high (ndarray) – function dependent of b at the lower temperature in °C and the higher frequency value in Hz

  • b_T_high_f_high (ndarray) – magnetic flux density at the higher temperature in °C and the higher frequency value in Hz

  • f_b_T_high_f_high (ndarray) – function dependent of b at the higher temperature in °C and the higher frequency value in Hz

  • no_interpolation_values (int) – number of interpolation values

  • y_label (str) – label of y-axes

  • plot (bool) – enable/disable plotting of data

Returns:

array of magnetic flux density, arrays of function dependent of b

materialdatabase.material_data_base_functions.interpolate_neighbours_linear(temperature: float, frequency: float, neighbours: dict)

Linear interpolation of frequency and temperature between neighbours.

Parameters:

  • temperature (float) – desired temperature value in °C

  • frequency (float) – desired frequency value in Hz

  • neighbours (dict) – neighbours

Returns:

amplitude of the permittivity, angle of the permittivity in degree

materialdatabase.material_data_base_functions.load_material_from_db(material_name: str) → None

Load data from material database.

Parameters:

material_name (str) – name of material

Returns:

all data of specific material

Return type:

dict

materialdatabase.material_data_base_functions.mu_phi_deg__from_mu_r_and_p_hyst(frequency: ndarray | float, b_peak: ndarray | float, mu_r: ndarray | float, p_hyst: ndarray | float)

Calculate the phase angle of the permeability given the peak value of the magnetic flux density, the hysteresis loss and the amplitude of permeability.

Parameters:

  • frequency (ndarray or float) – frequency in Hz

  • b_peak (ndarray or float) – peak flux density in T

  • mu_r (ndarray or float) – amplitude of the permeability in unitless

  • p_hyst (ndarray or float) – hysteresis losses in W/m^3

Returns:

phase angle of the permeability in degree

materialdatabase.material_data_base_functions.mu_r__from_p_hyst_and_mu_phi_deg(mu_phi_deg: ndarray | float, frequency: ndarray | float, b_peak: ndarray | float, p_hyst: ndarray | float)

Calculate the amplitude of the permeability given the peak value of the magnetic flux density, the hysteresis loss and the phase angle of the permeability.

Parameters:

  • mu_phi_deg (ndarray or float) – phase angle of the permeability in degree

  • frequency (ndarray or float) – frequency in Hz

  • b_peak (ndarray or float) – peak flux density in T

  • p_hyst (ndarray or float) – hysteresis losses in W/m^3

Returns:

amplitude of the permeability

materialdatabase.material_data_base_functions.my_interpolate_linear(a: float, b: float, f_a: float, f_b: float, x: float)

Interpolates linear between to points ‘a’ and ‘b’.

The return value is f_x in dependence of x It applies: a < x < b.

Parameters:

  • a (float) – x-value for point a

  • b (float) – x-value for point b

  • f_a (float) – y-value for point a

  • f_b (float) – y-value for point b

  • x (float) – x-value for the searched answer f_x

Returns:

y-value for given x-value

materialdatabase.material_data_base_functions.my_polate_linear(a: float, b: float, f_a: float, f_b: float, x: float)

Interpolates or extrapolates linear for a<x<b or x<a and x>b.

Parameters:

  • a (float) – input x-value for point a

  • b (float) – input x-value for point b

  • f_a (float) – input y-value for point a

  • f_b (float) – input y-value for point b

  • x (float) – x-value for the searched answer f_x

Returns:

y-value for given x-value

materialdatabase.material_data_base_functions.p_hyst__from_mu_r_and_mu_phi_deg(frequency: ndarray | float, b_peak: ndarray | float, mu_r: ndarray | float, mu_phi_deg: ndarray | float)

Calculate the hysteresis losses given the peak value of the magnetic flux density, the amplitude and phase angle of the permeability.

Parameters:

  • frequency (ndarray or float) – frequency in Hz

  • b_peak (ndarray or float) – peak flux density in T

  • mu_r (ndarray or float) – amplitude of the permeability in unitless

  • mu_phi_deg (ndarray or float) – phase angle of the permeability in degree

Returns:

hysteresis losses in W/m^3

materialdatabase.material_data_base_functions.plot_data(material_name: str | None = None, properties: str | None = None, b_ref: ndarray | list | None = None, mu_r_real: ndarray | list | None = None, mu_r_imag: ndarray | list | None = None)

Plot certain material properties of materials.

TODO: parameter is new and will probably cause problems when plotting data, but previous implementation was very static… :param material_name: name of the material :type material_name: str :param properties: name of the material properties :type properties: str :param b_ref: magnetic flux density value: :type b_ref: ndarray or list :param mu_r_real: real part of the permeability :type mu_r_real: ndarray or list :param mu_r_imag: imaginary part of the permeability :type mu_r_imag: ndarray or list

materialdatabase.material_data_base_functions.process_permeability_data(b_ref_raw: ndarray | list, mu_r_raw: ndarray | list, mu_phi_deg_raw: ndarray | list, b_min: float = 0.05, b_max: float = 0.3, smooth_data: bool = False, crop_data: bool = False, plot_data: bool = False, ax=None, f: float | None = None, T: float | None = None)

Post-Processing of raw data of the permeability.

Function can smooth, crop and plot the permeability data.

Parameters:

  • b_ref_raw (ndarray or float) – raw data of the magnetic flux density

  • mu_r_raw (ndarray or float) – raw data of the amplitude of the permeability

  • mu_phi_deg_raw (ndarray or float) – raw data of the angle of the permeability

  • b_min (float) – min value of the magnetic flux density for cropping

  • b_max (float) – max value of the magnetic flux density for cropping

  • smooth_data (bool) – enable/disable smoothing of data (savgol-filter)

  • crop_data (bool) – enable/disable cropping of data

  • plot_data (bool) – enable/disable plotting of data

  • ax (matplotlib.axes) – axes for plot

  • f (float) – frequency value in Hz

  • T (float) – temperature value in °C

Returns:

magnetic flux density and amplitude and angle of permeability

materialdatabase.material_data_base_functions.read_in_digitized_datasheet_plot(path: str)

Read in a csv-file containing the x- and y-data of a digitized plot from a manufacturer datasheet.

Information regarding Digitization:

  • used program: WebPlotDigitizer (made by Ankit Rohatgi)

  • delta_x = 8 Px

  • delta_y = 8 Px

  • format to save: Sort by: X

    Order: Ascending Digits: 5 Fixed Column Separator: ;

Parameters:

path (str) – path to csv-file

Returns:

list containing two lists with x- and y-data ([[“x-data”], [“y-data”]])

materialdatabase.material_data_base_functions.rect(radius_or_amplitude: ndarray | float, theta_deg: ndarray | float)

Convert polar coordinates [radius, angle] into cartesian coordinates [abscissa_x,ordinate_y].

Parameters:

  • radius_or_amplitude (ndarray or float) – radius or amplitude

  • theta_deg (ndarray or float) – angle in degree

Returns:

abscissa_x, ordinate_y

materialdatabase.material_data_base_functions.remove(arr: ndarray, n: int)

Remove duplicates from array.

Parameters:

  • arr (ndarray) – array with duplicates

  • n (int) – has no effect of the functionality

Returns:

array without duplicates

materialdatabase.material_data_base_functions.remove_mean_of_signal(signal: ndarray | None = None)

Remove the mean value of a signal.

Parameters:

signal (ndarray) – signal with mean value

Returns:

signal without mean value

materialdatabase.material_data_base_functions.sigma_from_permittivity(amplitude_relative_equivalent_permittivity: ndarray | float, phi_deg_relative_equivalent_permittivity: ndarray | float, frequency: ndarray | float)

Calculate the conductivity based on the data of the permittivity.

Parameters:

  • amplitude_relative_equivalent_permittivity (ndarray or float) – amplitude of the permittivity

  • phi_deg_relative_equivalent_permittivity (ndarray or float) – angle of the permittivity

  • frequency (nd array or float) – frequency value in Hz

Returns:

conductivity

materialdatabase.material_data_base_functions.sort_data(a: ndarray | list, b: ndarray | list, c: ndarray | list)

Sort three arrays according to array a.

Parameters:

  • a (ndarray or list) – array that is the base of the sorting

  • b (ndarray or list) – array that gets sorted based on a

  • c (ndarray or list) – array that gets sorted based on a

Returns:

the three arrays sorted according to a

materialdatabase.material_data_base_functions.store_data(material_name: str, data_to_be_stored: dict) → None

Store data from measurement/datasheet into the material database.

Parameters:

  • material_name (str) – name of the material

  • data_to_be_stored (dict) – data to be stored

materialdatabase.material_data_base_functions.updates_x_ticks_for_graph(x_data: ndarray | list, y_data: ndarray | list, x_new: ndarray | list | float, kind: str = 'linear')

Update the x-values of the given (x_data,y_data)-dataset and returns y_new based on x_new.

Parameters:

  • x_data (ndarray or list) – x-data given

  • y_data (ndarray or list) – y-data given

  • x_new (ndarray or list or float) – new x-values

  • kind (str) – kind of interpolation

Returns:

y_new-data corresponding to the x_new-data

materialdatabase.material_data_base_functions.write_permeability_data_into_database(frequency: float, temperature: float, b_ref: ndarray | list, mu_r_abs: ndarray | list, mu_phi_deg: ndarray | list, material_name: str, measurement_setup: str, current_shape: str = 'sine', H_DC_offset: float = 0, overwrite: bool = False)

Write permeability data into the material database.

CAUTION: This method only adds the given measurement series to the permeability data without checking duplicates.

Parameters:

  • frequency (float) – frequency value in Hz

  • temperature (float) – temperature value in °C

  • b_ref (ndarray or list) – magnetic flux density value

  • mu_r_abs (ndarray or list) – amplitude of the permeability

  • mu_phi_deg (ndarray or list) – angle of the permeability

  • material_name (str) – name of the material

  • measurement_setup (str) – name of the measurement setup

  • current_shape (str) – shape of the current (e.g. “sine”, “triangle”, “trapezoid”)

  • H_DC_offset (float) – offset in the magnetic field strength in A/m

  • overwrite (bool) – enable/disable overwritting of data

materialdatabase.material_data_base_functions.write_permittivity_data_into_database(temperature: float, frequencies: ndarray | list, epsilon_r: ndarray | list, epsilon_phi_deg: ndarray | list, material_name: str, measurement_setup: str)

Write permittivity data into the material database.

Parameters:

  • temperature (float) – measurement point of the temperature in °C

  • frequencies (ndarray or list) – measurement points of the frequency in Hz

  • epsilon_r (ndarray or list) – amplitude of the permittivity

  • epsilon_phi_deg (ndarray or list) – angle of the permittivity

  • material_name (str) – name of material

  • measurement_setup (str) – name of measurement setup

materialdatabase.material_data_base_functions.write_steinmetz_data_into_database(temperature: float, k: float, beta: float, alpha: float, material_name: str, measurement_setup: str)

Write steinmetz data into the material database.

CAUTION: This method only adds the given measurement series to the steinmetz data without checking duplicates.

Parameters:

  • temperature (float) – temperature value in °C

  • k (float) – k value of steinmetz parameters

  • beta (float) – beta value of the steinmetz parameters

  • alpha (float) – alpha value of the steinmetz parameters

  • material_name (str) – name of the material

  • measurement_setup (str) – name of the measurement setup