Model reduction of fractional impedance spectra for time–frequency analysis of batteries, fuel cells, and supercapacitors
Source abstract
Abstract
Abstract Joint time–frequency analysis is an emerging method for interpreting the underlying physics in fuel cells, batteries, and supercapacitors. To increase the reliability of time–frequency analysis, a theoretical correlation between frequency‐domain stationary analysis and time‐domain transient analysis is urgently required. The present work formularizes a thorough model reduction of fractional impedance spectra for electrochemical energy devices involving not only the model reduction from fractional‐order models to integer‐order models and from high‐ to low‐order RC circuits but also insight into the evolution of the characteristic time constants during the whole reduction process. The following work has been carried out: (i) the model‐reduction theory is addressed for typical Warburg elements and RC circuits based on the continued fraction expansion theory and the response error minimization technique, respectively; (ii) the order effect on the model reduction of typical Warburg elements is quantitatively evaluated by time–frequency analysis; (iii) the results of time–frequency analysis are confirmed to be useful to determine the reduction order in terms of the kinetic information needed to be captured; and (iv) the results of time–frequency analysis are validated for the model reduction of fractional impedance spectra for lithium‐ion batteries, supercapacitors, and solid oxide fuel cells. In turn, the numerical validation has demonstrated the powerful function of the joint time–frequency analysis. The thorough model reduction of fractional impedance spectra addressed in the present work not only clarifies the relationship between time‐domain transient analysis and frequency‐domain stationary analysis but also enhances the reliability of the joint time–frequency analysis for electrochemical energy devices.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Battery Technologies Research · Advanced Control Systems Design · Vibration Control and Rheological Fluids
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute for Sustainable Energy/College of Sciences Shanghai University Shanghai China
Shanxi Key Laboratory of Nanomaterials and Nanotechnology, School of Mechanical and Electrical Engineering Xi'an University of Architecture and Technology Xi'an Shaanxi China
Xi'an Key Laboratory of New Energy Materials and Devices, School of Materials Science and Engineering, Institute of Advanced Electrochemical Energy Xi'an University of Technology Xi'an Shaanxi China
Funding
National Natural Science Foundation of China
References (100+)
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