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IPM geometry optimization#

This example shows how to use PyAEDT to find the best machine 2D geometry to achieve high torque and low losses. The example shows how to setup an optimetrics analysis to sweep geometries for a single value of stator current angle. The torque and losses results are then exported in a .csv file.

Keywords: Maxwell 2D, transient, motor, optimization.

Perform imports and define constants#

Perform required imports.

[1]:

import csv
import os
import tempfile
import time

[2]:

import ansys.aedt.core

Define constants.

[3]:

AEDT_VERSION = "2024.2"
NUM_CORES = 4
NG_MODE = False  # Open AEDT UI when it is launched.

Create temporary directory and download files#

Create a temporary directory where downloaded data or dumped data can be stored. If you’d like to retrieve the project data for subsequent use, the temporary folder name is given by temp_folder.name.

[4]:

temp_folder = tempfile.TemporaryDirectory(suffix=".ansys")

Download AEDT file example#

Set the local temporary folder to export the AEDT file to.

[5]:

aedt_file = ansys.aedt.core.downloads.download_file(
    source="maxwell_motor_optimization",
    name="IPM_optimization.aedt",
    destination=temp_folder.name,
)

Launch Maxwell 2D#

Launch AEDT and Maxwell 2D after first setting up the project, the version and the graphical mode.

[6]:

m2d = ansys.aedt.core.Maxwell2d(
    project=aedt_file,
    version=AEDT_VERSION,
    new_desktop=True,
    non_graphical=NG_MODE,
)

PyAEDT INFO: Parsing C:\Users\ansys\AppData\Local\Temp\tmp6t8uqjwu.ansys\maxwell_motor_optimization\IPM_optimization.aedt.
PyAEDT INFO: Python version 3.10.11 (tags/v3.10.11:7d4cc5a, Apr  5 2023, 00:38:17) [MSC v.1929 64 bit (AMD64)]
PyAEDT INFO: PyAEDT version 0.12.dev0.
PyAEDT INFO: Initializing new Desktop session.
PyAEDT INFO: Log on console is enabled.
PyAEDT INFO: Log on file C:\Users\ansys\AppData\Local\Temp\pyaedt_ansys_ba7b8d45-c652-4ef0-8606-3bbe1182df39.log is enabled.
PyAEDT INFO: Log on AEDT is enabled.
PyAEDT INFO: Debug logger is disabled. PyAEDT methods will not be logged.
PyAEDT INFO: Launching PyAEDT with gRPC plugin.
PyAEDT INFO: New AEDT session is starting on gRPC port 53778
PyAEDT INFO: File C:\Users\ansys\AppData\Local\Temp\tmp6t8uqjwu.ansys\maxwell_motor_optimization\IPM_optimization.aedt correctly loaded. Elapsed time: 0m 0sec
PyAEDT INFO: AEDT installation Path C:\Program Files\AnsysEM\v242\Win64
PyAEDT INFO: Ansoft.ElectronicsDesktop.2024.2 version started with process ID 7448.
PyAEDT INFO: Project IPM_optimization has been opened.
PyAEDT INFO: Active Design set to M2D_Transient
PyAEDT INFO: Aedt Objects correctly read

Add parametric setup#

Add a parametric setup made up of geometry variable sweep definitions and single value for the stator current angle. Note: Step variations have been minimized to reduce the analysis time. If needed they can be increased by changing the step argument.

[7]:

param_sweep = m2d.parametrics.add(
    variable="bridge",
    start_point="0.5mm",
    end_point="1mm",
    step="0.5mm",
    variation_type="LinearStep",
)
param_sweep.add_variation(
    sweep_variable="din",
    start_point=70,
    end_point=80,
    step=10,
    units="mm",
    variation_type="LinearStep",
)
param_sweep.add_variation(
    sweep_variable="phase_advance",
    start_point=0,
    end_point=45,
    step=45,
    units="deg",
    variation_type="LinearStep",
)
param_sweep.add_variation(
    sweep_variable="Ipeak", start_point=200, units="A", variation_type="SingleValue"
)

[7]:

True

Analyze parametric sweep#

[8]:

param_sweep.analyze(cores=NUM_CORES)

PyAEDT INFO: Key Desktop/ActiveDSOConfigurations/Maxwell 2D correctly changed.
PyAEDT INFO: Solving Optimetrics
PyAEDT INFO: Key Desktop/ActiveDSOConfigurations/Maxwell 2D correctly changed.
PyAEDT INFO: Design setup Parametric_SRQ3BV solved correctly in 0.0h 11.0m 60.0s

[8]:

True

Post-processing#

Create reports to get torque and loss results for all variations.

[9]:

report_torque = m2d.post.create_report(
    expressions="Moving1.Torque",
    domain="Sweep",
    variations={"bridge": "All", "din": "All", "Ipeak": "All"},
    primary_sweep_variable="Time",
    plot_type="Rectangular Plot",
    plot_name="TorqueAllVariations",
)

PyAEDT INFO: Modeler2D class has been initialized!
PyAEDT INFO: Modeler class has been initialized! Elapsed time: 0m 0sec
PyAEDT INFO: PostProcessor class has been initialized! Elapsed time: 0m 0sec
PyAEDT INFO: Post class has been initialized! Elapsed time: 0m 0sec

[10]:

report_solid_loss = m2d.post.create_report(
    expressions="SolidLoss",
    domain="Sweep",
    variations={"bridge": "All", "din": "All", "Ipeak": "All"},
    primary_sweep_variable="Time",
    plot_type="Rectangular Plot",
    plot_name="SolidLossAllVariations",
)

[11]:

report_core_loss = m2d.post.create_report(
    expressions="CoreLoss",
    domain="Sweep",
    variations={"bridge": "All", "din": "All", "Ipeak": "All"},
    primary_sweep_variable="Time",
    plot_type="Rectangular Plot",
    plot_name="CoreLossAllVariations",
)

Get torque and loss solution data for all available variations.

[12]:

torque_data = m2d.post.get_solution_data(
    expressions=["Moving1.Torque"],
    setup_sweep_name=m2d.nominal_sweep,
    domain="Sweep",
    variations={"bridge": "All", "din": "All", "Ipeak": "All"},
    primary_sweep_variable="Time",
    report_category="Standard",
)

PyAEDT INFO: Solution Data Correctly Loaded.

[13]:

solid_loss_data = m2d.post.get_solution_data(
    expressions=["CoreLoss"],
    setup_sweep_name=m2d.nominal_sweep,
    domain="Sweep",
    variations={"bridge": "All", "din": "All", "Ipeak": "All"},
    primary_sweep_variable="Time",
    report_category="Standard",
)

PyAEDT INFO: Solution Data Correctly Loaded.

[14]:

core_loss_data = m2d.post.get_solution_data(
    expressions=["SolidLoss"],
    setup_sweep_name=m2d.nominal_sweep,
    domain="Sweep",
    variations={"bridge": "All", "din": "All", "Ipeak": "All"},
    primary_sweep_variable="Time",
    report_category="Standard",
)

PyAEDT INFO: Solution Data Correctly Loaded.

Calculate torque and loss average values for each variation and write data in a .csv file.

[15]:

csv_data = []
for var in core_loss_data.variations:
    torque_data.active_variation = var
    core_loss_data.active_variation = var
    solid_loss_data.active_variation = var

    torque_values = torque_data.data_magnitude()
    core_loss_values = core_loss_data.data_magnitude()
    solid_loss_values = solid_loss_data.data_magnitude()

    torque_data_average = sum(torque_values) / len(torque_values)
    core_loss_average = sum(core_loss_values) / len(core_loss_values)
    solid_loss_average = sum(solid_loss_values) / len(solid_loss_values)

    csv_data.append(
        {
            "active_variation": str(torque_data.active_variation),
            "average_torque": str(torque_data_average),
            "average_core_loss": str(core_loss_average),
            "average_solid_loss": str(solid_loss_average),
        }
    )

    with open(
        os.path.join(temp_folder.name, "motor_optimization.csv"), "w", newline=""
    ) as csvfile:
        fields = [
            "active_variation",
            "average_torque",
            "average_core_loss",
            "average_solid_loss",
        ]
        writer = csv.DictWriter(csvfile, fieldnames=fields)
        writer.writeheader()
        writer.writerows(csv_data)

Release AEDT#

[16]:

m2d.save_project()
m2d.release_desktop()
# Wait 3 seconds to allow AEDT to shut down before cleaning the temporary directory.
time.sleep(3)

PyAEDT INFO: Project IPM_optimization Saved correctly
PyAEDT INFO: Desktop has been released and closed.

Clean up#

All project files are saved in the folder temp_folder.name. If you’ve run this example as a Jupyter notebook, you can retrieve those project files. The following cell removes all temporary files, including the project folder.

[17]:

temp_folder.cleanup()

Download this example

Download this example as a Jupyter Notebook or as a Python script.