Alternatively, you may download this notebook and run it offline.
This notebook introduces functionality for simulating user case in which the experiment steps are triggered at a certain point in time.
%pip install "pybamm[plot,cite]" -q # install PyBaMM if it is not installed import pybamm from datetime import datetime
[notice] A new release of pip is available: 23.0.1 -> 23.1.2 [notice] To update, run: pip install --upgrade pip Note: you may need to restart the kernel to use updated packages.
Let’s start defining a model to illustrate this functionality, in this case we choose the SPM
model = pybamm.lithium_ion.SPM()
Usually we define an experiment such that each step is triggered when the previous step is completed. For example, in this case we do a 1C discharge for 20 minutes and then a C/3 charge for 10 minutes. The charge step starts after 20 minutes, i.e. once the discharge step is finished.
experiment = pybamm.Experiment(["Discharge at 1C for 20 minutes", "Charge at C/3 for 10 minutes"]) sim = pybamm.Simulation(model, experiment=experiment) sim.solve() sim.plot()
<pybamm.plotting.quick_plot.QuickPlot at 0x7f8910adb4f0>
However, if we want to represent a realistic user case we might certain experiments to be run at a certain time instead, even if that means cutting short the previous step. In this case we can pass a starting time as a keyword argument in the
pybamm.step.string method. The
start_time should be passed as a
s = pybamm.step.string experiment = pybamm.Experiment( [ s("Discharge at 1C for 1 hour", start_time=datetime(1, 1, 1, 8, 0, 0)), s("Charge at C/3 for 10 minutes", start_time=datetime(1, 1, 1, 8, 30, 0)), s("Discharge at C/2 for 30 minutes", start_time=datetime(1, 1, 1, 9, 0, 0)), s("Rest for 1 hour"), ] ) sim = pybamm.Simulation(model, experiment=experiment) sim.solve() sim.plot()
<pybamm.plotting.quick_plot.QuickPlot at 0x7f8910b8e250>
In the example above, we note that the first step (1C discharge) is cut short as the second step (C/3 charge) start time occurs before the end of the first step. On the other hand, an additional resting period is added after the second step as the third step (C/2 discharge) start time is 20 minutes later than the end of the second step. The final step does not have a start time so it is triggered immediately after the previous step. Note that if the argument
start_time is used in an
experiment, the first step should always have a
start_time, otherwise the solver will throw an error.
Note that you can use the
datetime.strptime (see the docs for more info) function to convert a string to a datetime object. For example, to start the experiment at 8:30 on the 2nd of January 2023, you can use
datetime.strptime("2023-01-02 8:30:00", "%Y-%m-%d %H:%M:%S")
datetime.datetime(2023, 1, 2, 8, 30)
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