20.500.12556/RUL-169866 Noise reduction with recursive filtering for more accurate parameter identification of electrochemical sources and interfaces Noise reduction is essential in analyzing electrochemical impedance spectroscopy (EIS) data for accurate parameter identification of models of electrochemical sources and interfaces. EIS is widely used to study the behavior of electrochemical systems as it provides information about the processes occurring at electrode surfaces. However, measurement noise can severely compromise the accuracy of parameter identification and the interpretation of EIS data. This paper presents methods for parameter identification of Randles (also known as R-RC or 2R-1C) equivalent electrical circuits and noise reduction in EIS data using recursive filtering. EIS data obtained at the estimated characteristic frequency is processed with three equations in the closed form for the parameter estimation of series resistance, charge transfer resistance, and double-layer capacitance. The proposed recursive filter enhances estimation accuracy in the presence of random noise. Filtering is embedded in the estimation procedure, while the optimal value of the recursive filter weighting factor is self-tuned based on the proposed search method. The distinguished feature is that the proposed method can process EIS data and perform estimation with filtering without any input from the user. Synthetic datasets and experimentally obtained impedance data of lithium-ion batteries were successfully processed using PC-based and microcontroller-based systems. electrochemical impedance spectroscopy R-RC circuit recursive filter equivalent circuit model noise reduction lithium-ion batteries elektrokemijska impedančna spektroskopija R-RC vezje rekurzivni filter ekvivalentni model vezja zmanjševanje šuma litij-ionske baterije true false true Angleški jezik Slovenski jezik Članek v reviji 2025-06-13 08:34:19 2025-06-13 08:34:20 2025-09-27 04:27:48 0000-00-00 00:00:00 2025 0 0 17 str. iss. 12, art. 3669 Vol. 25 Jun. 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 621.35:004 1424-8220 10.3390/s25123669 239220995 RAZ_Simic_Mitar_2025.pdf RAZ_Simic_Mitar_2025.pdf 1 750A2FC488A75F30C231396547D0C8C2 abcf4772650c956330de87c41c383da3fb6d292e6037a63f0b1d2d7c1f8c7d42 343096a2-9aa5-11f0-9328-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=218781 https://www.mdpi.com/1424-8220/25/12/3669 1 f0d59a29-481e-11f0-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=211614 Fakulteta za računalništvo in informatiko 0 0 0