Noise reduction with recursive filtering for more accurate parameter identification of electrochemical sources and interfaces

Simić, Mitar (avtor), Medić, Milan (avtor), Radovanović, Milan (avtor), Risojević, Vladimir (avtor), Bulić, Patricio (avtor)

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.

• Jezik: Angleški jezik
• Ključne besede: electrochemical impedance spectroscopy, R-RC circuit, recursive filter, equivalent circuit model, noise reduction, lithium-ion batteries
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FRI - Fakulteta za računalništvo in informatiko
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2025
• Št. strani: 17 str.
• Številčenje: Vol. 25, iss. 12, art. 3669
• PID: 20.500.12556/RUL-169866
• UDK: 621.35:004
• ISSN pri članku: 1424-8220
• DOI: 10.3390/s25123669
• COBISS.SI-ID: 239220995
• Datum objave v RUL: 13.06.2025

Gradivo je del revije

• Naslov: Sensors
• Skrajšan naslov: Sensors
• Založnik: MDPI
• ISSN: 1424-8220
• COBISS.SI-ID: 10176278

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: elektrokemijska impedančna spektroskopija, R-RC vezje, rekurzivni filter, ekvivalentni model vezja, zmanjševanje šuma, litij-ionske baterije

Projekti

• Financer: MESTD - Ministry of Education, Science and Technological Development of Republic of Serbia
• Številka projekta: 9.032/961-69/24
• Naslov: Signal Processing Using Embedded Systems and Machine Learning

• Financer: MESTD - Ministry of Education, Science and Technological Development of Republic of Serbia
• Številka projekta: 19/6-020/966-3-1/23
• Naslov: High-Performance Computing for Signal Processing