Hybrid stochastic-deterministic algorithms for the interpretation of Electrochemical Impedance Spectroscopy spectra of Proton Exchange Membrane Fuel Cells

•Stochastic algorithm output is used as initial value of deterministic NM algorithm.•Hybrid methods allow more reliable interpretation of PEMFC impedance data.•Hybrid methods allow to compare different EEC to identify the most suitable model.•Best approach for unknown order of magnitude of parameter...

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Vydáno v:	Electrochimica acta Ročník 518; s. 145673
Hlavní autoři:	Wu, P., Touhami, S., Aït-Idir, W., Yelloz, H., Marty, C., Micoud, F., Dillet, J., Lottin, O., Mainka, J.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.04.2025 Elsevier
Témata:	Electric power Electrochemical impedance spectroscopy (eis) Engineering Sciences Equivalent electrical circuit (eec) modeling Global Optimization Hybrid Algorithms Proton exchange membrane fuel cell (PEMFC) Global Optimization Proton exchange membrane fuel cell (PEMFC) Electrochemical impedance spectroscopy (eis) Equivalent electrical circuit (eec) modeling Hybrid Algorithms Proton exchange membrane fuel cell (PEMFC) Electrochemical impedance spectroscopy (eis) Equivalent electrical circuit (eec) modeling Global Optimization Hybrid Algorithms
ISSN:	0013-4686
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Popis
Shrnutí:	•Stochastic algorithm output is used as initial value of deterministic NM algorithm.•Hybrid methods allow more reliable interpretation of PEMFC impedance data.•Hybrid methods allow to compare different EEC to identify the most suitable model.•Best approach for unknown order of magnitude of parameters: PS-NM or GA-NM.•Best approach for known order of magnitude of parameters: SA-NM. This work presents a case study on the use of three hybrid algorithms combining a stochastic part -Genetic Algorithms (GA), Particle Swarm Optimization (PSO), or Simulated Annealing (SA)- with a deterministic Nelder-Mead (NM) algorithm for the estimation of the equivalent electrical circuit (EEC) parameters for the interpretation of Proton Exchange Membrane Fuel Cell (PEMFC) impedance data. These hybrid methods were evaluated on mathematical test functions as well as for the interpretation of simulated and experimental PEMFC impedance spectra using EEC of different complexity. The three stochastic/deterministic methods were compared in terms of stability, efficiency, ability to explore multiple solutions, and computing resources. The results showed that all hybrid methods were able to improve the interpretation of experimental EIS data by identifying satisfying and physically meaningful solutions, with low least-square residuals and by reducing the sensitivity to initial conditions while accelerating convergence. All methods allowed an improvement compared to the use of one single type of algorithm alone -deterministic and stochastic.
ISSN:	0013-4686
DOI:	10.1016/j.electacta.2025.145673