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Comparison of techniques based on frequency response analysis for state of health estimation in lithium-ion batteries

Wang, Shaojin (författare)
Wuhan University of Technology
Tang, Jinrui (författare)
Wuhan University of Technology
Xiong, Binyu (författare)
Wuhan University of Technology
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Fan, Junqiu (författare)
Guizhou University
Li, Yang, 1984 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Chen, Qihong (författare)
Wuhan University of Technology
Xie, Changjun (författare)
Wuhan University of Technology
Wei, Zhongbao (författare)
Beijing Institute of Technology
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 (creator_code:org_t)
2024
2024
Engelska.
Ingår i: Energy. - 0360-5442 .- 1873-6785. ; 304
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Frequency response analysis (FRA) methods are commonly used in the field of State of Health (SOH) estimation for Lithium-ion batteries (Libs). However, identifying their appropriate application scenarios can be challenging. This paper presents four FRA techniques, including electrochemical impedance spectra (EIS), mid-frequency and low-frequency domain equivalent circuit model (MLECM), distribution of relaxation time (DRT) and non-linear FRA (NFRA) technique. This paper proposes two estimation frameworks, machine learning and curve fitting, to be applied to each of the four techniques. Eight SOH estimation models are developed by linking the extracted feature parameters to the battery capacity variations. The paper compares the accuracy of estimation, estimation range, and other properties of the eight models. Application scenarios are identified for the techniques by using three classification methods: different estimation frameworks, frequency response linearity, and impedance technique. The results demonstrate that MLF is recommended for scenarios with a large amount of battery data, while CFF is recommended for scenarios with a small amount of data. NFRA could be applied to electric vehicle power batteries, while LFRA is recommended to be used for retired batteries. EIS method is recommended for complex and dynamic scenarios, while non-EIS method is recommended for scenarios that require high accuracy.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Nyckelord

Frequency response analysis
State of health estimation
Electrochemical impedance spectroscopy
Equivalent circuit model
Distribution of relaxation times

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