During the parameter identification of an equivalent circuit model for an electrochemical impedance spectrum (EIS), some bad points in the EIS seriously disturb the identification accuracy. We usually manually pick out those bad points according to our instinct or experience. I think this is very subjective. Does Anyone know any objective method or publications that i can count on to pick out the bad points?
To detect deviations from causality, linearity and stationarity requirements you can apply a special form of the Kramers-Kronig (KK) transform test called ZHIT (Zweipol Hilbert Transformation). Comparing the transfomated values with original measurement data allows you to define a maximum deviation beyond which you sort out bad points in your measured data.
The method is applied for example in this publication for lead acid batteries but works the same way for other electrochemical systems:
https://link.springer.com/article/10.1007/s10800-018-1217-z
I designed a workflow to automatically find 'bad points'. If u are interested, check out Article Automated workflow of EIS data validation and quality improv...
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