Georgia Southern University, [email protected] Southern University, [email protected] Southern University, [email protected] Follow this and additional works at: htps://digitalcommons.georgiasouthern.edu/electrical-eng-facpubsDepartment of Electrical Engineering, Georgia Southern University, Statesboro, GA, USA [email protected], [email protected], Abstract: Lead-Acid batteries continue to be the preferred choice for backup energy storage systems. However, the inherent variability in the manufacturing and component design processes affect the perform.
The lead-acid model has been proposed and explained in [ 21 ]. The Shepherd relation is the simplest and most popular battery model [ 7 ]. It defines the charging and discharging phases' nonlinearity. The discharge equation for a Lead acid battery is as follows:
Can RMSE be used to identify lead-acid battery parameters?
Conclusions This article suggests a recent method for identifying lead-acid battery parameters. This method updates the battery model with unknown parameters employing the metaheuristic algorithm algorithms. The identification compares the model output with actual measured data, and RMSE is utilized as an objective function.
How accurate is a lead-acid battery identification method?
The findings approve that the suggested identification method is excellent at precisely estimating the parameters of a lead-acid battery. In addition, the proposed method proved highly accurate compared to various algorithms and three testing cases. Conceptualization, H.R. and S.F.; methodology, H.R.,
How are battery parameters accurately identified using the proposed strategy?
The calculated and measured voltages are given in Figure 7. The model output voltage is identical to the measured battery voltage. Therefore, the battery parameters were accurately identified using the proposed strategy. Figure 7. Voltage curves of the battery model and the measured data.
The parameters of the model are derived from the discharge characteristics. The discharging and charging characteristics are assumed to be the same. The capacity of the battery does not change with the amplitude of the current (there is no Peukert effect). The self-discharge of the battery is not represented.
How accurate is the BES algorithm for estimating lead-acid battery parameters?
The BES achieved the best results in extracting the parameters of a 120 Ah Banner battery, compared to the other considered algorithms, which approve its performance in both robustness and accuracy. The findings approve that the suggested identification method is excellent at precisely estimating the parameters of a lead-acid battery.