Renewable energy is an alternative option that can be substituted for future energy demand. Many type of battery are used in commerce to propel portable power and this makes the task of selecting the right battery type is crucial. This paper presents the analysis of voltage charging and discharging for lead acid battery using time-frequency distribution (TFD) which is spectrogram. Spectogram technique is used to represent the signals in the time-frequency representation (TFR). The parameter of a signal such as instantaneous root mean square (RMS) voltage, direct current voltage (VDC) and alternating current voltage (VAC) are estimated from the TFR to identify the signal characteristics. This analysis, focus on lead-acid battery with nominal battery voltage of 6 and 12V and storage capacity from 5 until 50Ah. The battery is a model using MATLAB/SIMULINK and the results show that spectrogram technique is capable to identify and determine the signal characteristic of Lead Acid battery.
Batteries are essential components of most electrical devices and one of the most important parameters in batteries is storage capacity. It represents the maximum amount of energy that can be extracted from the battery under certain specified condition. This paper presents the analysis of charging and discharging battery signal using periodogram. The periodogram converts waveform data from the time domain into the frequency domain and represents the distribution of the signal power over frequency. This analysis focuses on four types of batteries which are lead-acid (LA), lithium-ion (Li-ion), nickel-cadmium (Ni-Cd) and nickel-metal-hydride (Ni-MH). This paper used battery model from MATLAB/SIMULINK software and the nominal voltage of each battery is 6 and 12V while the capacity is 10 and 20Ah, respectively. The analysis is done and the result shows that varying capacity produce different power at a frequency and voltage at DC component.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.