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 (V RMS (t)), instantaneous direct current voltage (V DC (t)) and

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... tantaneous alternating current voltage (V AC (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 V AC (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.