Fitting procedure based on Differential Evolution to evaluate impedance parameters of metal–coating systems. Issue 9 (16th July 2019)

• Record Type: Journal Article
• Authors: González, Francisco; Greiner, David; Mena, Vicente; Souto, Ricardo M.; Santana, Juan J.; Aznárez, Juan J.
• Is Part Of: Engineering computations. Volume 36:Issue 9(2019)
• Page Start: 2960
• Page End: 2982
• Publication Date: 2019-07-16
• Subjects: Differential Evolution -- Evolutionary algorithms -- Electrochemical impedance spectroscopy -- Electrical equivalent circuit parameters -- Metal–coating systems -- Modelling studies; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-11-2018-0513
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose: Impedance data obtained by electrochemical impedance spectroscopy ( EIS ) are fitted to a relevant electrical equivalent circuit to evaluate parameters directly related to the resistance and the durability of metal–coating systems. The purpose of this study is to present a novel and more efficient computational strategy for the modelling of EIS measurements using the Differential Evolution paradigm. Design/methodology/approach: An alternative method to non-linear regression algorithms for the analysis of measured data in terms of equivalent circuit parameters is provided by evolutionary algorithms, particularly the Differential Evolution ( DE ) algorithms (standard DE and a representative of the self-adaptive DE paradigm were used). Findings: The results obtained with DE algorithms were compared with those yielding from commercial fitting software, achieving a more accurate solution, and a better parameter identification, in all the cases treated. Further, an enhanced fitting power for the modelling of metal–coating systems was obtained. Originality/value: The great potential of the developed tool has been demonstrated in the analysis of the evolution of EIS spectra due to progressive degradation of metal–coating systems. Open codes of the different differential algorithms used are included, and also, examples tackled in the document are open. It allows the complete use, or improvement, of the developed tool by researchers.