EIS data are generally analyzed in terms of an equivalent-circuit model. The analyst tries to find a model whose impedance matches the measured data.
The type of electrical components in the model and their interconnections controls the shape of the model's impedance spectrum. The model's parameters (i.e, the resistance value of a resistor) controls the size of each feature in the spectrum. Both these factors affect the degree to which the model's impedance spectrum matches a measured EIS spectrum.
In a physical model, each of the model's components is postulated to come from a physical process in the electrochemical cell. All of the models discussed earlier in this section are physical models. The choice of which physical model applies to a given cell is made from knowledge of the cell's physical characteristics. Experienced EIS analysts use the shape of a cell's EIS spectrum to help choose among possible physical models for that cell.
Models can also be partially or completely empirical. The circuit components in this type of model are not assigned to physical processes in the cell. The model is chosen to given the best possible match between the model's impedance and the measured impedance.
An empirical model can be constructed by successively subtracting component impedances from a spectrum. If the subtraction of an impedance simplifies the spectrum, the component is added to the model, and the next component impedance is subtracted from the simplified spectrum. This process ends when the spectrum is completely gone (Z = 0).
As we shall see, physical models are generally preferable to empirical models.