Internal Resistance Estimation of Li-ion Batteries using Wavelet Analysis

Roberta Di Fonso; Pallavi Bharadwaj; Remus Teodorescu; Carlo Cecati

doi:10.1109/PEDG54999.2022.9923094

Internal Resistance Estimation of Li-ion Batteries using Wavelet Analysis

Roberta Di Fonso, Pallavi Bharadwaj, Remus Teodorescu, Carlo Cecati

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

8 Citations (Scopus)

Abstract

Lithium ion batteries have high energy density, long life cycle and light weight, which makes them the perfect choice for electric vehicles (EVs). Battery performances degrade with usage and time and this translates into a decreased charge capacity and an increased internal resistance. Internal resistance is directly related to the amount of deliverable power, therefore its estimation is of particular interest for EVs. In this paper, time-frequency wavelet analysis will be used to detect the fast transients of the output voltage of the battery in order to estimate the internal resistance. The effectiveness of the proposed method is verified on the publicly available dataset from the Prognostics Data Repository of NASA.

Original language	English
Title of host publication	2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022
Publisher	IEEE (Institute of Electrical and Electronics Engineers)
Publication date	2022
ISBN (Electronic)	9781665466189
DOIs	https://doi.org/10.1109/PEDG54999.2022.9923094
Publication status	Published - 2022
Event	13th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022 - Kiel, Germany Duration: 26 Jun 2022 → 29 Jun 2022

Conference

Conference	13th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022
Country/Territory	Germany
City	Kiel
Period	26/06/2022 → 29/06/2022

Series	2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022

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Publisher Copyright:
© 2022 IEEE.

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Di Fonso, Roberta ; Bharadwaj, Pallavi ; Teodorescu, Remus et al. / Internal Resistance Estimation of Li-ion Batteries using Wavelet Analysis. 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022. IEEE (Institute of Electrical and Electronics Engineers), 2022. (2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022).

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title = "Internal Resistance Estimation of Li-ion Batteries using Wavelet Analysis",

abstract = "Lithium ion batteries have high energy density, long life cycle and light weight, which makes them the perfect choice for electric vehicles (EVs). Battery performances degrade with usage and time and this translates into a decreased charge capacity and an increased internal resistance. Internal resistance is directly related to the amount of deliverable power, therefore its estimation is of particular interest for EVs. In this paper, time-frequency wavelet analysis will be used to detect the fast transients of the output voltage of the battery in order to estimate the internal resistance. The effectiveness of the proposed method is verified on the publicly available dataset from the Prognostics Data Repository of NASA.",

author = "{Di Fonso}, Roberta and Pallavi Bharadwaj and Remus Teodorescu and Carlo Cecati",

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doi = "10.1109/PEDG54999.2022.9923094",

language = "English",

series = "2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022",

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Di Fonso, R, Bharadwaj, P, Teodorescu, R & Cecati, C 2022, Internal Resistance Estimation of Li-ion Batteries using Wavelet Analysis. in 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022. IEEE (Institute of Electrical and Electronics Engineers), 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022, 13th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022, Kiel, Germany, 26/06/2022. https://doi.org/10.1109/PEDG54999.2022.9923094

Internal Resistance Estimation of Li-ion Batteries using Wavelet Analysis. / Di Fonso, Roberta; Bharadwaj, Pallavi; Teodorescu, Remus et al.
2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022. IEEE (Institute of Electrical and Electronics Engineers), 2022. (2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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T1 - Internal Resistance Estimation of Li-ion Batteries using Wavelet Analysis

AU - Di Fonso, Roberta

AU - Bharadwaj, Pallavi

AU - Teodorescu, Remus

AU - Cecati, Carlo

PY - 2022

Y1 - 2022

N2 - Lithium ion batteries have high energy density, long life cycle and light weight, which makes them the perfect choice for electric vehicles (EVs). Battery performances degrade with usage and time and this translates into a decreased charge capacity and an increased internal resistance. Internal resistance is directly related to the amount of deliverable power, therefore its estimation is of particular interest for EVs. In this paper, time-frequency wavelet analysis will be used to detect the fast transients of the output voltage of the battery in order to estimate the internal resistance. The effectiveness of the proposed method is verified on the publicly available dataset from the Prognostics Data Repository of NASA.

AB - Lithium ion batteries have high energy density, long life cycle and light weight, which makes them the perfect choice for electric vehicles (EVs). Battery performances degrade with usage and time and this translates into a decreased charge capacity and an increased internal resistance. Internal resistance is directly related to the amount of deliverable power, therefore its estimation is of particular interest for EVs. In this paper, time-frequency wavelet analysis will be used to detect the fast transients of the output voltage of the battery in order to estimate the internal resistance. The effectiveness of the proposed method is verified on the publicly available dataset from the Prognostics Data Repository of NASA.

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M3 - Article in proceeding

AN - SCOPUS:85142022074

T3 - 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022

BT - 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022

PB - IEEE (Institute of Electrical and Electronics Engineers)

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Di Fonso R, Bharadwaj P, Teodorescu R, Cecati C. Internal Resistance Estimation of Li-ion Batteries using Wavelet Analysis. In 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022. IEEE (Institute of Electrical and Electronics Engineers). 2022. (2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022). doi: 10.1109/PEDG54999.2022.9923094

Internal Resistance Estimation of Li-ion Batteries using Wavelet Analysis

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