BattMo.jl

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Example with SEI layer ​

Preparation of the input ​

julia
using Jutul, BattMo, GLMakie

We use the SEI model presented in [1]. We use the json data given in bolay.json which contains the parameters for the SEI layer.

julia
cell_parameters = load_cell_parameters(; from_default_set = "chen_2020")
cycling_protocol = load_cycling_protocol(; from_default_set = "cccv")
simulation_settings = load_simulation_settings(; from_default_set = "p2d")

We have a look at the SEI related parameters.

julia
interphase_parameters = cell_parameters["NegativeElectrode"]["Interphase"]
Dict{String, Any} with 8 entries:
  "Description"                    => "EC-based SEI, from Bolay2022."
  "ElectronicDiffusionCoefficient" => 1.6e-12
  "InterstitialConcentration"      => 0.015
  "InitialThickness"               => 1.0e-8
  "IonicConductivity"              => 1.0e-5
  "StoichiometricCoefficient"      => 2
  "InitialPotentialDrop"           => 0.5
  "MolarVolume"                    => 9.586e-5

We start the simulation and retrieve the result ​

julia
model = LithiumIonBattery();

model_settings = model.settings
model_settings["SEIModel"] = "Bolay"

cycling_protocol["TotalNumberOfCycles"] = 10

sim = Simulation(model, cell_parameters, cycling_protocol; simulation_settings);

output = solve(sim)

t = output.time_series["Time"]
E = output.time_series["Voltage"]
I = output.time_series["Current"]
✔️ Validation of ModelSettings passed: No issues found.
──────────────────────────────────────────────────
✔️ Validation of CellParameters passed: No issues found.
──────────────────────────────────────────────────
✔️ Validation of CyclingProtocol passed: No issues found.
──────────────────────────────────────────────────
✔️ Validation of SimulationSettings passed: No issues found.
──────────────────────────────────────────────────
✔️ Validation of SolverSettings passed: No issues found.
──────────────────────────────────────────────────
Jutul: Simulating 2 days, 2 hours as 3600 report steps
╭────────────────┬────────────┬────────────────┬──────────────╮
│ Iteration type │   Avg/step │   Avg/ministep │        Total │
│                │ 2630 steps │ 2806 ministeps │     (wasted) │
├────────────────┼────────────┼────────────────┼──────────────┤
│ Newton         │    3.01179 │        2.82288 │  7921 (2140) │
│ Linearization  │    4.07871 │        3.82288 │ 10727 (2247) │
│ Linear solver  │    3.01179 │        2.82288 │  7921 (2140) │
│ Precond apply  │        0.0 │            0.0 │        0 (0) │
╰────────────────┴────────────┴────────────────┴──────────────╯
╭───────────────┬────────┬────────────┬─────────╮
│ Timing type   │   Each │   Relative │   Total │
│               │     ms │ Percentage │       s │
├───────────────┼────────┼────────────┼─────────┤
│ Properties    │ 0.1217 │     3.69 % │  0.9637 │
│ Equations     │ 1.3470 │    55.38 % │ 14.4497 │
│ Assembly      │ 0.3115 │    12.81 % │  3.3409 │
│ Linear solve  │ 0.4831 │    14.67 % │  3.8270 │
│ Linear setup  │ 0.0000 │     0.00 % │  0.0000 │
│ Precond apply │ 0.0000 │     0.00 % │  0.0000 │
│ Update        │ 0.1367 │     4.15 % │  1.0830 │
│ Convergence   │ 0.1807 │     7.43 % │  1.9379 │
│ Input/Output  │ 0.0393 │     0.42 % │  0.1103 │
│ Other         │ 0.0477 │     1.45 % │  0.3781 │
├───────────────┼────────┼────────────┼─────────┤
│ Total         │ 3.2939 │   100.00 % │ 26.0906 │
╰───────────────┴────────┴────────────┴─────────╯

Plot of voltage and current ​

julia
plot_dashboard(output; plot_type = "simple")

Plot of SEI thickness ​

We recover the SEI thickness from the state output

julia
seilength_x1 = output.states["SEIThickness"][:, 1]
seilength_xend = output.states["SEIThickness"][:, end]

f = Figure(size = (1000, 400))

ax = Axis(f[1, 1],
	title = "Length",
	xlabel = "Time / s",
	ylabel = "Thickness / m",
	xlabelsize = 25,
	ylabelsize = 25,
	xticklabelsize = 25,
	yticklabelsize = 25,
)

scatterlines!(ax,
	t,
	seilength_x1;
	linewidth = 4,
	markersize = 10,
	marker = :cross,
	markercolor = :black)

scatterlines!(ax,
	t,
	seilength_xend;
	linewidth = 4,
	markersize = 10,
	marker = :cross,
	markercolor = :black)

ax = Axis(f[2, 1],
	title = "SEI thicknesss",
	xlabel = "Time / s",
	ylabel = "Voltage / V",
	xlabelsize = 25,
	ylabelsize = 25,
	xticklabelsize = 25,
	yticklabelsize = 25,
)

scatterlines!(ax,
	t,
	E;
	linewidth = 4,
	markersize = 10,
	marker = :cross,
	markercolor = :black)

Plot of voltage drop ​

julia
u_x1 = output.states["SEIVoltageDrop"][:, 1]
u_xend = output.states["SEIVoltageDrop"][:, end]

f = Figure(size = (1000, 400))

ax = Axis(f[1, 1],
	title = "SEI voltage drop",
	xlabel = "Time / s",
	ylabel = "Voltage / V",
	xlabelsize = 25,
	ylabelsize = 25,
	xticklabelsize = 25,
	yticklabelsize = 25,
)

scatterlines!(ax,
	t,
	u_x1;
	linewidth = 4,
	markersize = 10,
	marker = :cross,
	markercolor = :blue,
	label = "xmin")

scatterlines!(ax,
	t,
	u_xend;
	linewidth = 4,
	markersize = 10,
	marker = :cross,
	markercolor = :black,
	label = "xmax")
Plot{Makie.scatterlines, Tuple{Vector{Point{2, Float64}}}}

Example on GitHub ​

If you would like to run this example yourself, it can be downloaded from the BattMo.jl GitHub repository as a script.

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