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Lead Acid Battery Analysis using S-Transform

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@article{IJASEIT2289,
   author = {Muhammad Sufyan Safwan Mohamad Basir and Abdul Rahim Abdullah and Nur Asmiza Selamat and Haslinda Musa and Rahifa Ranom},
   title = {Lead Acid Battery Analysis using S-Transform},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {7},
   number = {5},
   year = {2017},
   pages = {1832--1839},
   keywords = {lead acid; equivalent circuit model; S-Transform; time-frequency representation},
   abstract = {This paper proposes a new signal processing technique using time-frequency distribution (TFD), namely S-transform (ST) for battery parameters estimation. Compared to other TFDs such as short time Fourier transform (STFT) and wavelet transform (WT), ST technique offers more promising results in a low frequency application analysis, especially battery. The results of the ST are the parameters of instantaneous means square voltage (VRMS (t)), instantaneous direct current voltage (VDC (t)) and instantaneous alternating current voltage (VAC (t)) extracted from the time-frequency representation (TFR). Simulation through MATLAB has been conducted using equivalent circuit model (ECM), using 12 V lead acid (LA) battery with capacities from 1.0 Ah to 10.0 Ah. For the battery model, charging/discharging signal has been used to estimate the battery parameters from the ST technique to determine battery characteristics. From the signal characteristics of battery capacity versus VAC (t) obtained, new equation is proposed based on the curve fitting tool. The advantage of this technique embraces a better capability in estimating battery parameters at low frequency component, resulting in better frequency and time resolutions compared to previous TFDs.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=2289},
   doi = {10.18517/ijaseit.7.5.2289}
}

EndNote

%A Mohamad Basir, Muhammad Sufyan Safwan
%A Abdullah, Abdul Rahim
%A Selamat, Nur Asmiza
%A Musa, Haslinda
%A Ranom, Rahifa
%D 2017
%T Lead Acid Battery Analysis using S-Transform
%B 2017
%9 lead acid; equivalent circuit model; S-Transform; time-frequency representation
%! Lead Acid Battery Analysis using S-Transform
%K lead acid; equivalent circuit model; S-Transform; time-frequency representation
%X This paper proposes a new signal processing technique using time-frequency distribution (TFD), namely S-transform (ST) for battery parameters estimation. Compared to other TFDs such as short time Fourier transform (STFT) and wavelet transform (WT), ST technique offers more promising results in a low frequency application analysis, especially battery. The results of the ST are the parameters of instantaneous means square voltage (VRMS (t)), instantaneous direct current voltage (VDC (t)) and instantaneous alternating current voltage (VAC (t)) extracted from the time-frequency representation (TFR). Simulation through MATLAB has been conducted using equivalent circuit model (ECM), using 12 V lead acid (LA) battery with capacities from 1.0 Ah to 10.0 Ah. For the battery model, charging/discharging signal has been used to estimate the battery parameters from the ST technique to determine battery characteristics. From the signal characteristics of battery capacity versus VAC (t) obtained, new equation is proposed based on the curve fitting tool. The advantage of this technique embraces a better capability in estimating battery parameters at low frequency component, resulting in better frequency and time resolutions compared to previous TFDs.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=2289
%R doi:10.18517/ijaseit.7.5.2289
%J International Journal on Advanced Science, Engineering and Information Technology
%V 7
%N 5
%@ 2088-5334

IEEE

Muhammad Sufyan Safwan Mohamad Basir,Abdul Rahim Abdullah,Nur Asmiza Selamat,Haslinda Musa and Rahifa Ranom,"Lead Acid Battery Analysis using S-Transform," International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 5, pp. 1832-1839, 2017. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.7.5.2289.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Mohamad Basir, Muhammad Sufyan Safwan
AU  - Abdullah, Abdul Rahim
AU  - Selamat, Nur Asmiza
AU  - Musa, Haslinda
AU  - Ranom, Rahifa
PY  - 2017
TI  - Lead Acid Battery Analysis using S-Transform
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 7 (2017) No. 5
Y2  - 2017
SP  - 1832
EP  - 1839
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - lead acid; equivalent circuit model; S-Transform; time-frequency representation
N2  - This paper proposes a new signal processing technique using time-frequency distribution (TFD), namely S-transform (ST) for battery parameters estimation. Compared to other TFDs such as short time Fourier transform (STFT) and wavelet transform (WT), ST technique offers more promising results in a low frequency application analysis, especially battery. The results of the ST are the parameters of instantaneous means square voltage (VRMS (t)), instantaneous direct current voltage (VDC (t)) and instantaneous alternating current voltage (VAC (t)) extracted from the time-frequency representation (TFR). Simulation through MATLAB has been conducted using equivalent circuit model (ECM), using 12 V lead acid (LA) battery with capacities from 1.0 Ah to 10.0 Ah. For the battery model, charging/discharging signal has been used to estimate the battery parameters from the ST technique to determine battery characteristics. From the signal characteristics of battery capacity versus VAC (t) obtained, new equation is proposed based on the curve fitting tool. The advantage of this technique embraces a better capability in estimating battery parameters at low frequency component, resulting in better frequency and time resolutions compared to previous TFDs.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=2289
DO  - 10.18517/ijaseit.7.5.2289

RefWorks

RT Journal Article
ID 2289
A1 Mohamad Basir, Muhammad Sufyan Safwan
A1 Abdullah, Abdul Rahim
A1 Selamat, Nur Asmiza
A1 Musa, Haslinda
A1 Ranom, Rahifa
T1 Lead Acid Battery Analysis using S-Transform
JF International Journal on Advanced Science, Engineering and Information Technology
VO 7
IS 5
YR 2017
SP 1832
OP 1839
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 lead acid; equivalent circuit model; S-Transform; time-frequency representation
AB This paper proposes a new signal processing technique using time-frequency distribution (TFD), namely S-transform (ST) for battery parameters estimation. Compared to other TFDs such as short time Fourier transform (STFT) and wavelet transform (WT), ST technique offers more promising results in a low frequency application analysis, especially battery. The results of the ST are the parameters of instantaneous means square voltage (VRMS (t)), instantaneous direct current voltage (VDC (t)) and instantaneous alternating current voltage (VAC (t)) extracted from the time-frequency representation (TFR). Simulation through MATLAB has been conducted using equivalent circuit model (ECM), using 12 V lead acid (LA) battery with capacities from 1.0 Ah to 10.0 Ah. For the battery model, charging/discharging signal has been used to estimate the battery parameters from the ST technique to determine battery characteristics. From the signal characteristics of battery capacity versus VAC (t) obtained, new equation is proposed based on the curve fitting tool. The advantage of this technique embraces a better capability in estimating battery parameters at low frequency component, resulting in better frequency and time resolutions compared to previous TFDs.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=2289
DO  - 10.18517/ijaseit.7.5.2289