State of charge calculation of lead acid battery
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Estimation of State of Charge (SOC) of batteries plays a vital role in
Battery Management Systems(BMS). It is important to enhance the lifetime
of a battery and give the user an accurate estimation of available
runtime. This study aims to estimate the battery SOC based on current
through and voltage across a battery using Support Vector Regression
(SVR). Tests are run on SIMULINK using a 6 V, 4.5 Ah Lead Acid battery.
Hyper parameters that decide the accuracy of SVR are estimated using
Grid Search and Particle Swarm Optimization (PSO). The SVR maintains a
high level of accuracy, with a Mean Squared Error (MSE) of 0.45% for PSO
and 0.95% for GS.
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