Parametric dynamic twin evaluation

This example shows how you can use PyTwin to load and evaluate a twin model and simulate multiple parametric variations. The model is used for determining the range of an electric vehicle. The vehicle is represented by a battery, the electric loads of the vehicle, and an electric machine connected to a simple 1D chassis. The driver controls the vehicle speed to follow a repeated sequence of the WLTP cycle (class 3). The mass of the vehicle and the electric power loads are parameterized so that their effects on the overall electric range can be seen.

# sphinx_gallery_thumbnail_path = '_static/electricRange.png'

Perform required imports

Perform required imports, which include downloading and importing the input files.

import matplotlib.pyplot as plt
import pandas as pd
from pytwin import TwinModel, download_file

twin_file = download_file("ElectricRange_23R1_other.twin", "twin_files", force_download=True)

Define auxiliary functions

Define auxiliary functions for comparing and plotting the results from different parametric simulations executed on the same twin model.

def plot_result_comparison(results: list[pd.DataFrame], sweep: list[dict]):
    """Compare the results obtained from the different parametric simulations executed
    on the same TwinModel. The results datasets are provided as Pandas dataframes. The
    function plots the results for a few variables of particular interest."""

    pd.set_option("display.precision", 12)
    pd.set_option("display.max_columns", 20)
    pd.set_option("display.expand_frame_repr", False)

    color = ["g", "b", "r"]
    # Output ordering: time, battery_loss, loads_loss, machine_loss, pack_SoC, position,
    # speed_m, speed_ref, tau_ref, tau_sns
    x0_ind = 0
    y0_ind = 6
    z0_ind = 7
    x1_ind = 4
    y1_ind = 5

    # Plot the runtime outputs for two results: the drive cycle and the distance
    # achieved versus the battery state of the charge for all parametric variations
    fig, ax = plt.subplots(ncols=1, nrows=2, figsize=(18, 7))

    fig.subplots_adjust(hspace=0.5)
    fig.set_tight_layout({"pad": 0.0})

    axes0 = ax[0]

    results[0].plot(x=x0_ind, y=y0_ind, ax=axes0, label="{}".format("measured speed"))
    results[0].plot(x=x0_ind, y=z0_ind, ax=axes0, ls="-.", label="{}".format("reference speed"))

    axes0.set_title("Drive cycle")
    axes0.set_xlabel(results[0].columns[x0_ind] + " [sec]")
    axes0.set_ylabel(results[0].columns[y0_ind] + " [m/s]")
    axes0.set_xlim((0, 32 * 60))

    axes1 = ax[1]

    for ind, dp in enumerate(sweep):
        # Plot runtime results
        results[ind].plot(x=x1_ind, y=y1_ind, ax=axes1, color=color[ind], label="{}".format(dp))

    axes1.set_title("Range/distance achieved vs battery SoC")
    axes1.set_xlabel(results[0].columns[x1_ind])
    axes1.set_xlim((0.1, 0.9))
    axes1.set_ylabel(results[0].columns[y1_ind] + " [m]")

    # Show plot
    plt.show()

Load the twin runtime and instantiate it

Load the twin runtime and instantiate it.

print("Loading model: {}".format(twin_file))
twin_model = TwinModel(twin_file)

Loading model: C:\Users\ansys\AppData\Local\Temp\TwinExamples\twin_files\ElectricRange_23R1_other.twin

Define inputs and simulation settings

Define the inputs and simulation settings.

time_step = 1.0
time_end = 24000.0  # Simulate the model for 400 minutes
print("Twin parameters : {}".format(twin_model.parameters))
dp1 = {"ElectricRange_powerLoad": 2000.0, "ElectricRange_vehicleMass": 2000.0}
dp2 = {"ElectricRange_powerLoad": 3000.0, "ElectricRange_vehicleMass": 2000.0}
dp3 = {"ElectricRange_powerLoad": 2000.0, "ElectricRange_vehicleMass": 1500.0}
sweep = [dp1, dp2, dp3]

Twin parameters : {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}

Simulate the twin for each set of parameter values

Simulate the twin for each set of parameters values for each time step and collect corresponding output values.

results = []
for dp in sweep:
    # Initialize twin model with the correct parameters values and collect
    # initial output values

    twin_model.initialize_evaluation(parameters=dp)
    outputs = [twin_model.evaluation_time]
    for item in twin_model.outputs:
        outputs.append(twin_model.outputs[item])
    sim_output = [outputs]
    while twin_model.evaluation_time < time_end:
        step = time_step
        twin_model.evaluate_step_by_step(step_size=step)
        outputs = [twin_model.evaluation_time]
        for item in twin_model.outputs:
            outputs.append(twin_model.outputs[item])
        sim_output.append(outputs)
        if twin_model.evaluation_time % 1000 == 0.0:
            print(
                "Simulating the model with parameters {}, evaluation time = {}".format(dp, twin_model.evaluation_time)
            )
    sim_results = pd.DataFrame(sim_output, columns=["Time"] + list(twin_model.outputs), dtype=float)
    results.append(sim_results)

Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 1000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 2000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 3000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 4000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 5000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 6000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 7000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 8000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 9000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 10000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 11000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 12000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 13000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 14000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 15000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 16000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 17000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 18000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 19000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 20000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 21000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 22000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 23000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 24000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 1000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 2000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 3000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 4000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 5000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 6000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 7000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 8000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 9000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 10000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 11000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 12000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 13000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 14000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 15000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 16000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 17000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 18000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 19000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 20000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 21000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 22000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 23000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 3000.0, 'ElectricRange_vehicleMass': 2000.0}, evaluation time = 24000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 1000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 2000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 3000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 4000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 5000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 6000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 7000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 8000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 9000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 10000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 11000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 12000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 13000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 14000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 15000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 16000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 17000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 18000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 19000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 20000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 21000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 22000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 23000.0
Simulating the model with parameters {'ElectricRange_powerLoad': 2000.0, 'ElectricRange_vehicleMass': 1500.0}, evaluation time = 24000.0

Plot results

Plot the results and save the images on disk.

plot_result_comparison(results, sweep)