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A Comparative Study On Spectrogram And S-Transform For Batteries Parameters Estimation

This research presents the analysis of battery charging and discharging signals using spectrogram, and S-transform techniques. The analysed batteries are lead acid (LA), nickel-metal hydride (Ni-MH), and lithium-ion (Li-ion). From the equivalent circuit model (ECM) simulated using MATLAB, the consta...

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Main Authors: Mohamad Basir, Muhammad Sufyan Safwan, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah
Format: Article
Language:English
Published: Penerbit UTM Press 2019
Online Access:http://eprints.utem.edu.my/id/eprint/24628/2/12801-38678-1-PB.PDF
http://eprints.utem.edu.my/id/eprint/24628/
https://journals.utm.my/jurnalteknologi/article/view/12801/6506
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spelling my.utem.eprints.246282020-12-08T14:26:25Z http://eprints.utem.edu.my/id/eprint/24628/ A Comparative Study On Spectrogram And S-Transform For Batteries Parameters Estimation Mohamad Basir, Muhammad Sufyan Safwan Abdullah, Abdul Rahim Mohd Saad, Norhashimah This research presents the analysis of battery charging and discharging signals using spectrogram, and S-transform techniques. The analysed batteries are lead acid (LA), nickel-metal hydride (Ni-MH), and lithium-ion (Li-ion). From the equivalent circuit model (ECM) simulated using MATLAB, the constant charging and discharging signals are presented, jointly, in time-frequency representation (TFR). From the TFR, the battery signal characteristics are determined from the estimated parameters of instantaneous means square voltage (V RMS (t)), instantaneous direct current voltage (V DC (t)), and instantaneous alternating current voltage (V AC (t)). Hence, an equation for battery remaining capacity as a function of estimated parameter of V AC (t) using curve fitting tool is presented. In developing a real-time automated battery parameters estimation system, the best time-frequency distribution (TFD) is chosen in terms of accuracy of the battery parameters, computational complexity in signal processing, and memory size. The advantages in high accuracy for battery parameters estimation, and low in memory size requirement makes the S-transform technique is selected to be the best TFD. Then, field testing is conducted for different cases, and the results show that the average mean absolute percentage error (MAPE) calculated is around 4%. Penerbit UTM Press 2019-03 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/24628/2/12801-38678-1-PB.PDF Mohamad Basir, Muhammad Sufyan Safwan and Abdullah, Abdul Rahim and Mohd Saad, Norhashimah (2019) A Comparative Study On Spectrogram And S-Transform For Batteries Parameters Estimation. Jurnal Teknologi, 81 (2). pp. 113-122. ISSN 0127-9696 https://journals.utm.my/jurnalteknologi/article/view/12801/6506 10.11113/jt.v81.12801
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description This research presents the analysis of battery charging and discharging signals using spectrogram, and S-transform techniques. The analysed batteries are lead acid (LA), nickel-metal hydride (Ni-MH), and lithium-ion (Li-ion). From the equivalent circuit model (ECM) simulated using MATLAB, the constant charging and discharging signals are presented, jointly, in time-frequency representation (TFR). From the TFR, the battery signal characteristics are determined from the estimated parameters of instantaneous means square voltage (V RMS (t)), instantaneous direct current voltage (V DC (t)), and instantaneous alternating current voltage (V AC (t)). Hence, an equation for battery remaining capacity as a function of estimated parameter of V AC (t) using curve fitting tool is presented. In developing a real-time automated battery parameters estimation system, the best time-frequency distribution (TFD) is chosen in terms of accuracy of the battery parameters, computational complexity in signal processing, and memory size. The advantages in high accuracy for battery parameters estimation, and low in memory size requirement makes the S-transform technique is selected to be the best TFD. Then, field testing is conducted for different cases, and the results show that the average mean absolute percentage error (MAPE) calculated is around 4%.
format Article
author Mohamad Basir, Muhammad Sufyan Safwan
Abdullah, Abdul Rahim
Mohd Saad, Norhashimah
spellingShingle Mohamad Basir, Muhammad Sufyan Safwan
Abdullah, Abdul Rahim
Mohd Saad, Norhashimah
A Comparative Study On Spectrogram And S-Transform For Batteries Parameters Estimation
author_facet Mohamad Basir, Muhammad Sufyan Safwan
Abdullah, Abdul Rahim
Mohd Saad, Norhashimah
author_sort Mohamad Basir, Muhammad Sufyan Safwan
title A Comparative Study On Spectrogram And S-Transform For Batteries Parameters Estimation
title_short A Comparative Study On Spectrogram And S-Transform For Batteries Parameters Estimation
title_full A Comparative Study On Spectrogram And S-Transform For Batteries Parameters Estimation
title_fullStr A Comparative Study On Spectrogram And S-Transform For Batteries Parameters Estimation
title_full_unstemmed A Comparative Study On Spectrogram And S-Transform For Batteries Parameters Estimation
title_sort comparative study on spectrogram and s-transform for batteries parameters estimation
publisher Penerbit UTM Press
publishDate 2019
url http://eprints.utem.edu.my/id/eprint/24628/2/12801-38678-1-PB.PDF
http://eprints.utem.edu.my/id/eprint/24628/
https://journals.utm.my/jurnalteknologi/article/view/12801/6506
_version_ 1687397253520556032
score 13.211869

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