Parameter estimation of a lead-acid battery model using genetic algorithm - Freitas, David Ciarlini; Silva, Hugerles Sales; Neto, Edson Cavalcanti; Lima, Antonio Marcus Nogueira (Journal of Mechatronics Engineering, 2019)
Lead-Acid batteries models classifications are shown. The battery model used and its charging and discharging equations are shown. These equations are expanded to find the value of the time constant of this model, which is fixed at a given value. A genetic algorithm is applied to these expanded equations to estimate the value of the time constant. Some battery charging and discharging cycles are used for estimation and validation of the proposed system. A time constant other than the previously set value is found. A simulation study is used to demonstrate the feasibility of the proposed parameter determination method.