PyInductor

An unofficial Python port of Serge Stroobandt, ON4AA's "Single-Layer Helical Round Wire Coil Inductor Calculator" (JavaScript here) with a few other additions (parameter tuning, temperature effects and sensitivity analysis).

This might be useful to some for designing air-core wire inductors (or helical antennas) for RF applications.

8/2021 update: Filip Valder (fivaldi on GitHub) added Python 3 support, unit tests and experimental phasing coil solver.

1/2019 update: Serge Stroobandt has ported his code from JavaScript to Brython (browser Python), so have a look.

Requirements

Python 3.8
Python 2.7 (deprecated)
SciPy
NumPy
Matplotlib (only for plotting, can be removed with small changes)

Differences

A notable difference is that this version requires the diameter of the coil former (diam_former) instead of the diameter of the former plus the wire. The additional temperature model is first order and only applies to the resistivity and physical dimensions of the wire, so be wary of this limitation.

Note that the results obtained with this version don't always match the original's (likely due to porting bugs) and that almost nothing has been properly validated, so proceed with caution. Also this port is possibly a bit outdated since the original may have been modified since its creation.

Usage

The most basic usage takes the physical dimensions, material properties and frequency of the inductor and returns a dictionary of calculated values (inductance, resonant frequency, etc.)

For example:

from inductor import Inductor, MATERIALS

params = dict(N=6, diam_former=3e-3, diam_wire=1e-3, f=10e6, len_coil=8e-3)
params.update(MATERIALS['Cu, annealed'])

ind = Inductor(**params)
results = ind.analyze()

print results

gives:

{'Rs_equiv': 0.0260142920022588, 'char_impedance': 1062.8882724816337, 'Ls_equiv': 4.18213766576639e-08, 'Rs_eff': 0.03933132499704669, 'Q_eff': 82.14705604747247, 'res_freq': 1088325440.0625987, 'Q_equiv': 101.01042124023245, 'skin_depth': 2.1102261245635593e-05, 'prop_factor': 0.5173362883660613, 'Ls_eff': 5.142220706528976e-08, 'Cp_equiv': 1.1309733366263994e-09}

For an explanation of these quantities see here, and note in particular the difference between the effective series inducance (Ls_eff) and the frequency-independent equivalent inductance (Ls_equiv).

Tuning support is useful if you want to obtain (say) the necessary coil length for a desired inductance:

from inductor import Inductor, MATERIALS

L_desired = 50e-9 # design a 50 nH inductor
params = dict(N=4, diam_former=5e-3, diam_wire=1.2e-3, f=100e6, len_coil=51e-3)
params.update(MATERIALS['Cu, annealed'])

ind = Inductor(**params)
print 'Initial length = %0.3f mm -> inductance = %0.3f nH' % (ind.len_coil/1e-3, ind.analyze()['Ls_eff']/1e-9)

ind.tune_parameter('len_coil', L_desired, input_range=(1e-3, 1))
print 'Tuned length = %0.3f mm -> inductance = %0.3f nH' % (ind.len_coil/1e-3, ind.analyze()['Ls_eff']/1e-9)

gives:

Initial length = 51.000 mm -> inductance = 94.515 nH
Tuned length = 10.838 mm -> inductance = 50.000 nH

You can also analyze the effect of changing an arbitrary input parameter (length, temperature, frequency, etc.) on an output quantity (inductance, Q, sensitivity, etc.). For example, you can obtain plots of the Q and self resonant frequency vs. wire diameter, while varying the length to fix the inductance:

You can also see how it affects the temperature coefficient of the inductance:

Development and testing

Install tox (virtualenv-based automation of test activities) and run it in the root of the repository:
```
% tox
```

Credit and license

All credit to Serge Stroobandt for his original version. License falls under his original GNU GPL version 3.