A novel self-adaptive state of charge (SOC) estimation model of lead-acid batteries based on Unscented Kalman Filter (UKF) algorithm is presented in here. The model state and measurement equations are constituted by the Ah counting method and load voltage method. In order to ensure the estimation accuracy, we establish a new function model for the Variable Rated Capacity of lead-acid batteries, and so the Ah counting method has been improved. On this basis, the SOC Algorithm is compared in three experimental conditions (including constant-current, constant-voltage and pulse-charge/discharge). The results show that this algorithm can effectively estimate SOC.
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